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# roberta-base-mnli-combined-multivalue

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the GLUE MNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3918
- Accuracy: 0.8569

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 1.1005        | 0.01  | 500    | 1.0983          | 0.3366   |
| 1.0983        | 0.02  | 1000   | 1.0925          | 0.3553   |
| 1.0308        | 0.03  | 1500   | 0.9173          | 0.5742   |
| 0.8148        | 0.04  | 2000   | 0.6755          | 0.7252   |
| 0.6979        | 0.05  | 2500   | 0.6042          | 0.7605   |
| 0.6274        | 0.06  | 3000   | 0.5757          | 0.7740   |
| 0.6115        | 0.07  | 3500   | 0.5600          | 0.7833   |
| 0.5549        | 0.08  | 4000   | 0.5196          | 0.8014   |
| 0.5681        | 0.09  | 4500   | 0.4972          | 0.8069   |
| 0.553         | 0.1   | 5000   | 0.4781          | 0.8109   |
| 0.5422        | 0.11  | 5500   | 0.5118          | 0.8064   |
| 0.5385        | 0.12  | 6000   | 0.4821          | 0.8136   |
| 0.5271        | 0.13  | 6500   | 0.4645          | 0.8179   |
| 0.5022        | 0.14  | 7000   | 0.4794          | 0.8182   |
| 0.4973        | 0.15  | 7500   | 0.5009          | 0.8149   |
| 0.503         | 0.16  | 8000   | 0.4590          | 0.8220   |
| 0.5054        | 0.17  | 8500   | 0.4745          | 0.8258   |
| 0.5007        | 0.18  | 9000   | 0.4605          | 0.8246   |
| 0.4988        | 0.19  | 9500   | 0.4377          | 0.8302   |
| 0.4853        | 0.2   | 10000  | 0.4459          | 0.8315   |
| 0.4877        | 0.21  | 10500  | 0.4546          | 0.8251   |
| 0.4729        | 0.22  | 11000  | 0.4619          | 0.8287   |
| 0.4848        | 0.23  | 11500  | 0.4518          | 0.8244   |
| 0.4849        | 0.24  | 12000  | 0.4914          | 0.8286   |
| 0.4793        | 0.25  | 12500  | 0.4583          | 0.8296   |
| 0.4846        | 0.26  | 13000  | 0.4247          | 0.8367   |
| 0.4736        | 0.28  | 13500  | 0.4730          | 0.8217   |
| 0.4758        | 0.29  | 14000  | 0.4596          | 0.8261   |
| 0.4951        | 0.3   | 14500  | 0.4421          | 0.8357   |
| 0.4662        | 0.31  | 15000  | 0.4583          | 0.8324   |
| 0.4779        | 0.32  | 15500  | 0.4264          | 0.8406   |
| 0.4672        | 0.33  | 16000  | 0.4496          | 0.8267   |
| 0.477         | 0.34  | 16500  | 0.4235          | 0.8388   |
| 0.4589        | 0.35  | 17000  | 0.4788          | 0.8235   |
| 0.4622        | 0.36  | 17500  | 0.4387          | 0.8284   |
| 0.4741        | 0.37  | 18000  | 0.4556          | 0.8387   |
| 0.4381        | 0.38  | 18500  | 0.4394          | 0.8372   |
| 0.4597        | 0.39  | 19000  | 0.4143          | 0.8412   |
| 0.443         | 0.4   | 19500  | 0.4318          | 0.8377   |
| 0.4437        | 0.41  | 20000  | 0.4359          | 0.8362   |
| 0.436         | 0.42  | 20500  | 0.4440          | 0.8332   |
| 0.4366        | 0.43  | 21000  | 0.4155          | 0.8453   |
| 0.4536        | 0.44  | 21500  | 0.4283          | 0.8461   |
| 0.4433        | 0.45  | 22000  | 0.4513          | 0.8344   |
| 0.4321        | 0.46  | 22500  | 0.4238          | 0.8460   |
| 0.4332        | 0.47  | 23000  | 0.4640          | 0.8368   |
| 0.434         | 0.48  | 23500  | 0.4230          | 0.8433   |
| 0.4355        | 0.49  | 24000  | 0.4378          | 0.8443   |
| 0.4379        | 0.5   | 24500  | 0.4087          | 0.8431   |
| 0.4336        | 0.51  | 25000  | 0.4328          | 0.8440   |
| 0.4205        | 0.52  | 25500  | 0.4387          | 0.8393   |
| 0.4161        | 0.53  | 26000  | 0.4205          | 0.8413   |
| 0.4217        | 0.54  | 26500  | 0.4266          | 0.8379   |
| 0.4145        | 0.55  | 27000  | 0.4220          | 0.8416   |
| 0.405         | 0.56  | 27500  | 0.4228          | 0.8454   |
| 0.428         | 0.57  | 28000  | 0.4255          | 0.8483   |
| 0.4113        | 0.58  | 28500  | 0.4181          | 0.8485   |
| 0.4112        | 0.59  | 29000  | 0.4191          | 0.8475   |
| 0.4276        | 0.6   | 29500  | 0.4102          | 0.8457   |
| 0.4197        | 0.61  | 30000  | 0.4098          | 0.8495   |
| 0.4132        | 0.62  | 30500  | 0.4300          | 0.8478   |
| 0.4164        | 0.63  | 31000  | 0.4296          | 0.8362   |
| 0.4062        | 0.64  | 31500  | 0.4368          | 0.8381   |
| 0.4123        | 0.65  | 32000  | 0.4221          | 0.8436   |
| 0.4022        | 0.66  | 32500  | 0.4062          | 0.8478   |
| 0.4063        | 0.67  | 33000  | 0.4414          | 0.8416   |
| 0.3973        | 0.68  | 33500  | 0.4106          | 0.8483   |
| 0.4095        | 0.69  | 34000  | 0.3999          | 0.8505   |
| 0.4006        | 0.7   | 34500  | 0.4306          | 0.8514   |
| 0.3982        | 0.71  | 35000  | 0.4110          | 0.8530   |
| 0.4193        | 0.72  | 35500  | 0.4158          | 0.8478   |
| 0.394         | 0.73  | 36000  | 0.4135          | 0.8477   |
| 0.4009        | 0.74  | 36500  | 0.4211          | 0.8559   |
| 0.3997        | 0.75  | 37000  | 0.4229          | 0.8404   |
| 0.4054        | 0.76  | 37500  | 0.4251          | 0.8500   |
| 0.3907        | 0.77  | 38000  | 0.4208          | 0.8513   |
| 0.3827        | 0.78  | 38500  | 0.4399          | 0.8427   |
| 0.3943        | 0.79  | 39000  | 0.4497          | 0.8399   |
| 0.3901        | 0.8   | 39500  | 0.4174          | 0.8496   |
| 0.3905        | 0.81  | 40000  | 0.4100          | 0.8504   |
| 0.4034        | 0.83  | 40500  | 0.4259          | 0.8505   |
| 0.3761        | 0.84  | 41000  | 0.4022          | 0.8492   |
| 0.3777        | 0.85  | 41500  | 0.3925          | 0.8561   |
| 0.3775        | 0.86  | 42000  | 0.4287          | 0.8550   |
| 0.3835        | 0.87  | 42500  | 0.4055          | 0.8493   |
| 0.384         | 0.88  | 43000  | 0.4081          | 0.8550   |
| 0.3719        | 0.89  | 43500  | 0.4131          | 0.8511   |
| 0.3799        | 0.9   | 44000  | 0.4096          | 0.8507   |
| 0.389         | 0.91  | 44500  | 0.4160          | 0.8532   |
| 0.3835        | 0.92  | 45000  | 0.3972          | 0.8556   |
| 0.3813        | 0.93  | 45500  | 0.4134          | 0.8538   |
| 0.371         | 0.94  | 46000  | 0.4574          | 0.8506   |
| 0.3762        | 0.95  | 46500  | 0.4067          | 0.8496   |
| 0.3813        | 0.96  | 47000  | 0.4100          | 0.8526   |
| 0.3694        | 0.97  | 47500  | 0.3969          | 0.8499   |
| 0.3971        | 0.98  | 48000  | 0.4142          | 0.8531   |
| 0.3661        | 0.99  | 48500  | 0.4106          | 0.8532   |
| 0.3787        | 1.0   | 49000  | 0.4162          | 0.8529   |
| 0.321         | 1.01  | 49500  | 0.4591          | 0.8494   |
| 0.314         | 1.02  | 50000  | 0.4458          | 0.8539   |
| 0.3079        | 1.03  | 50500  | 0.4392          | 0.8560   |
| 0.2967        | 1.04  | 51000  | 0.4482          | 0.8501   |
| 0.3062        | 1.05  | 51500  | 0.4355          | 0.8502   |
| 0.3037        | 1.06  | 52000  | 0.4790          | 0.8528   |
| 0.3143        | 1.07  | 52500  | 0.4456          | 0.8513   |
| 0.3055        | 1.08  | 53000  | 0.4474          | 0.8521   |
| 0.295         | 1.09  | 53500  | 0.4733          | 0.8495   |
| 0.3046        | 1.1   | 54000  | 0.4562          | 0.8594   |
| 0.3131        | 1.11  | 54500  | 0.4519          | 0.8533   |
| 0.3022        | 1.12  | 55000  | 0.4392          | 0.8576   |
| 0.2858        | 1.13  | 55500  | 0.4498          | 0.8534   |
| 0.3044        | 1.14  | 56000  | 0.4417          | 0.8496   |
| 0.2957        | 1.15  | 56500  | 0.4497          | 0.8593   |
| 0.3063        | 1.16  | 57000  | 0.4504          | 0.8551   |
| 0.3001        | 1.17  | 57500  | 0.4671          | 0.8526   |
| 0.3137        | 1.18  | 58000  | 0.4186          | 0.8559   |
| 0.2918        | 1.19  | 58500  | 0.4568          | 0.8583   |
| 0.302         | 1.2   | 59000  | 0.4533          | 0.8569   |
| 0.2944        | 1.21  | 59500  | 0.4400          | 0.8505   |
| 0.295         | 1.22  | 60000  | 0.4876          | 0.8576   |
| 0.3083        | 1.23  | 60500  | 0.4565          | 0.8496   |
| 0.3003        | 1.24  | 61000  | 0.4779          | 0.8516   |
| 0.3007        | 1.25  | 61500  | 0.4405          | 0.8603   |
| 0.2849        | 1.26  | 62000  | 0.4665          | 0.8543   |
| 0.2957        | 1.27  | 62500  | 0.4501          | 0.8509   |
| 0.2893        | 1.28  | 63000  | 0.4618          | 0.8525   |
| 0.2994        | 1.29  | 63500  | 0.4217          | 0.8538   |
| 0.2848        | 1.3   | 64000  | 0.4569          | 0.8608   |
| 0.3062        | 1.31  | 64500  | 0.4445          | 0.8517   |
| 0.3033        | 1.32  | 65000  | 0.4486          | 0.8527   |
| 0.2919        | 1.33  | 65500  | 0.4366          | 0.8550   |
| 0.294         | 1.34  | 66000  | 0.4745          | 0.8525   |
| 0.3094        | 1.35  | 66500  | 0.4593          | 0.8561   |
| 0.2928        | 1.36  | 67000  | 0.4660          | 0.8558   |
| 0.2934        | 1.38  | 67500  | 0.4348          | 0.8570   |
| 0.2903        | 1.39  | 68000  | 0.4804          | 0.8520   |
| 0.3052        | 1.4   | 68500  | 0.4554          | 0.8564   |
| 0.2944        | 1.41  | 69000  | 0.4287          | 0.8573   |
| 0.2867        | 1.42  | 69500  | 0.4141          | 0.8546   |
| 0.2953        | 1.43  | 70000  | 0.5205          | 0.8515   |
| 0.303         | 1.44  | 70500  | 0.4617          | 0.8500   |
| 0.2919        | 1.45  | 71000  | 0.4243          | 0.8555   |
| 0.2769        | 1.46  | 71500  | 0.4479          | 0.8506   |
| 0.2825        | 1.47  | 72000  | 0.4671          | 0.8573   |
| 0.2809        | 1.48  | 72500  | 0.4770          | 0.8572   |
| 0.2789        | 1.49  | 73000  | 0.4434          | 0.8528   |
| 0.2865        | 1.5   | 73500  | 0.4788          | 0.8536   |
| 0.2914        | 1.51  | 74000  | 0.4250          | 0.8587   |
| 0.2778        | 1.52  | 74500  | 0.4679          | 0.8583   |
| 0.2798        | 1.53  | 75000  | 0.4451          | 0.8542   |
| 0.2821        | 1.54  | 75500  | 0.4699          | 0.8575   |
| 0.2888        | 1.55  | 76000  | 0.4190          | 0.8588   |
| 0.297         | 1.56  | 76500  | 0.4692          | 0.8599   |
| 0.2927        | 1.57  | 77000  | 0.4465          | 0.8575   |
| 0.2788        | 1.58  | 77500  | 0.4531          | 0.8579   |
| 0.2871        | 1.59  | 78000  | 0.4216          | 0.8569   |
| 0.2724        | 1.6   | 78500  | 0.4848          | 0.8515   |
| 0.2775        | 1.61  | 79000  | 0.4835          | 0.8548   |
| 0.28          | 1.62  | 79500  | 0.4978          | 0.8557   |
| 0.2987        | 1.63  | 80000  | 0.4339          | 0.8579   |
| 0.2877        | 1.64  | 80500  | 0.4577          | 0.8558   |
| 0.2938        | 1.65  | 81000  | 0.4640          | 0.8582   |
| 0.2686        | 1.66  | 81500  | 0.4475          | 0.8606   |
| 0.2771        | 1.67  | 82000  | 0.4663          | 0.8524   |
| 0.2789        | 1.68  | 82500  | 0.4413          | 0.8577   |
| 0.2855        | 1.69  | 83000  | 0.4490          | 0.8522   |
| 0.2741        | 1.7   | 83500  | 0.4751          | 0.8547   |
| 0.2859        | 1.71  | 84000  | 0.4891          | 0.8520   |
| 0.2761        | 1.72  | 84500  | 0.4924          | 0.8545   |
| 0.2654        | 1.73  | 85000  | 0.4823          | 0.8521   |
| 0.2774        | 1.74  | 85500  | 0.4432          | 0.8561   |
| 0.2667        | 1.75  | 86000  | 0.4519          | 0.8500   |
| 0.2748        | 1.76  | 86500  | 0.4956          | 0.8500   |
| 0.2771        | 1.77  | 87000  | 0.4315          | 0.8556   |
| 0.2661        | 1.78  | 87500  | 0.5186          | 0.8529   |
| 0.2744        | 1.79  | 88000  | 0.5249          | 0.8504   |
| 0.277         | 1.8   | 88500  | 0.4780          | 0.8548   |
| 0.2782        | 1.81  | 89000  | 0.4763          | 0.8575   |
| 0.2736        | 1.82  | 89500  | 0.4585          | 0.8577   |
| 0.2662        | 1.83  | 90000  | 0.4679          | 0.8566   |
| 0.2594        | 1.84  | 90500  | 0.5044          | 0.8522   |
| 0.2684        | 1.85  | 91000  | 0.4698          | 0.8552   |
| 0.2639        | 1.86  | 91500  | 0.5030          | 0.8532   |
| 0.2707        | 1.87  | 92000  | 0.4859          | 0.8521   |
| 0.2605        | 1.88  | 92500  | 0.4907          | 0.8526   |
| 0.2649        | 1.89  | 93000  | 0.4844          | 0.8548   |
| 0.2627        | 1.9   | 93500  | 0.4541          | 0.8552   |
| 0.2636        | 1.91  | 94000  | 0.4497          | 0.8580   |
| 0.259         | 1.93  | 94500  | 0.4748          | 0.8505   |
| 0.2607        | 1.94  | 95000  | 0.4909          | 0.8559   |
| 0.2623        | 1.95  | 95500  | 0.4954          | 0.8571   |
| 0.2742        | 1.96  | 96000  | 0.4420          | 0.8585   |
| 0.2545        | 1.97  | 96500  | 0.4562          | 0.8564   |
| 0.2623        | 1.98  | 97000  | 0.5162          | 0.8490   |
| 0.2669        | 1.99  | 97500  | 0.4562          | 0.8526   |
| 0.2625        | 2.0   | 98000  | 0.4853          | 0.8583   |
| 0.2155        | 2.01  | 98500  | 0.6241          | 0.8550   |
| 0.2043        | 2.02  | 99000  | 0.6258          | 0.8565   |
| 0.1968        | 2.03  | 99500  | 0.6347          | 0.8522   |
| 0.212         | 2.04  | 100000 | 0.5714          | 0.8580   |
| 0.1921        | 2.05  | 100500 | 0.5958          | 0.8569   |
| 0.1981        | 2.06  | 101000 | 0.6816          | 0.8543   |
| 0.1998        | 2.07  | 101500 | 0.6267          | 0.8544   |
| 0.2105        | 2.08  | 102000 | 0.5886          | 0.8590   |
| 0.2004        | 2.09  | 102500 | 0.6216          | 0.8577   |
| 0.2045        | 2.1   | 103000 | 0.6211          | 0.8551   |
| 0.2129        | 2.11  | 103500 | 0.5851          | 0.8594   |
| 0.2001        | 2.12  | 104000 | 0.6792          | 0.8468   |
| 0.2222        | 2.13  | 104500 | 0.5870          | 0.8554   |
| 0.2081        | 2.14  | 105000 | 0.5643          | 0.8592   |
| 0.2073        | 2.15  | 105500 | 0.5265          | 0.8596   |
| 0.2118        | 2.16  | 106000 | 0.6301          | 0.8549   |
| 0.211         | 2.17  | 106500 | 0.5945          | 0.8622   |
| 0.2029        | 2.18  | 107000 | 0.6731          | 0.8509   |
| 0.2073        | 2.19  | 107500 | 0.6049          | 0.8552   |
| 0.2051        | 2.2   | 108000 | 0.5709          | 0.8616   |
| 0.1987        | 2.21  | 108500 | 0.5796          | 0.8601   |
| 0.208         | 2.22  | 109000 | 0.6507          | 0.8576   |
| 0.2081        | 2.23  | 109500 | 0.6255          | 0.8557   |
| 0.2063        | 2.24  | 110000 | 0.5992          | 0.8512   |
| 0.2112        | 2.25  | 110500 | 0.5834          | 0.8519   |
| 0.2114        | 2.26  | 111000 | 0.5814          | 0.8532   |
| 0.1993        | 2.27  | 111500 | 0.6537          | 0.8559   |
| 0.2153        | 2.28  | 112000 | 0.5545          | 0.8602   |
| 0.1983        | 2.29  | 112500 | 0.5710          | 0.8558   |
| 0.2132        | 2.3   | 113000 | 0.5757          | 0.8576   |
| 0.2058        | 2.31  | 113500 | 0.6018          | 0.8530   |
| 0.2051        | 2.32  | 114000 | 0.6388          | 0.8523   |
| 0.2005        | 2.33  | 114500 | 0.6415          | 0.8532   |
| 0.2187        | 2.34  | 115000 | 0.6010          | 0.8553   |
| 0.1978        | 2.35  | 115500 | 0.6147          | 0.8567   |
| 0.2136        | 2.36  | 116000 | 0.5904          | 0.8547   |
| 0.1997        | 2.37  | 116500 | 0.5887          | 0.8544   |
| 0.1919        | 2.38  | 117000 | 0.6138          | 0.8578   |
| 0.1959        | 2.39  | 117500 | 0.6519          | 0.8546   |
| 0.2079        | 2.4   | 118000 | 0.6237          | 0.8551   |
| 0.2045        | 2.41  | 118500 | 0.6382          | 0.8561   |
| 0.1963        | 2.42  | 119000 | 0.6502          | 0.8550   |
| 0.2039        | 2.43  | 119500 | 0.6160          | 0.8554   |
| 0.2086        | 2.44  | 120000 | 0.6367          | 0.8553   |
| 0.2007        | 2.45  | 120500 | 0.6417          | 0.8546   |
| 0.2113        | 2.46  | 121000 | 0.6231          | 0.8583   |
| 0.2037        | 2.48  | 121500 | 0.6063          | 0.8550   |
| 0.212         | 2.49  | 122000 | 0.5978          | 0.8544   |
| 0.2126        | 2.5   | 122500 | 0.5809          | 0.8567   |
| 0.1935        | 2.51  | 123000 | 0.6117          | 0.8534   |
| 0.205         | 2.52  | 123500 | 0.6242          | 0.8527   |
| 0.1931        | 2.53  | 124000 | 0.6220          | 0.8538   |
| 0.1973        | 2.54  | 124500 | 0.6151          | 0.8523   |
| 0.2002        | 2.55  | 125000 | 0.6011          | 0.8542   |
| 0.2041        | 2.56  | 125500 | 0.6344          | 0.8551   |
| 0.1919        | 2.57  | 126000 | 0.6695          | 0.8519   |
| 0.2025        | 2.58  | 126500 | 0.6053          | 0.8556   |
| 0.2047        | 2.59  | 127000 | 0.6209          | 0.8530   |
| 0.1956        | 2.6   | 127500 | 0.6641          | 0.8553   |
| 0.2004        | 2.61  | 128000 | 0.5823          | 0.8581   |
| 0.2035        | 2.62  | 128500 | 0.6495          | 0.8565   |
| 0.2038        | 2.63  | 129000 | 0.6086          | 0.8608   |
| 0.2081        | 2.64  | 129500 | 0.6034          | 0.8528   |
| 0.1965        | 2.65  | 130000 | 0.5650          | 0.8587   |
| 0.2072        | 2.66  | 130500 | 0.6245          | 0.8614   |
| 0.2001        | 2.67  | 131000 | 0.6267          | 0.8615   |
| 0.1984        | 2.68  | 131500 | 0.6314          | 0.8536   |
| 0.1991        | 2.69  | 132000 | 0.6229          | 0.8583   |
| 0.1904        | 2.7   | 132500 | 0.6191          | 0.8562   |
| 0.1945        | 2.71  | 133000 | 0.6019          | 0.8604   |
| 0.2044        | 2.72  | 133500 | 0.5939          | 0.8598   |
| 0.2017        | 2.73  | 134000 | 0.5907          | 0.8546   |
| 0.1952        | 2.74  | 134500 | 0.5762          | 0.8564   |
| 0.1921        | 2.75  | 135000 | 0.5756          | 0.8551   |
| 0.1986        | 2.76  | 135500 | 0.6371          | 0.8573   |
| 0.19          | 2.77  | 136000 | 0.6144          | 0.8567   |
| 0.1932        | 2.78  | 136500 | 0.7048          | 0.8524   |
| 0.1932        | 2.79  | 137000 | 0.6870          | 0.8494   |
| 0.1979        | 2.8   | 137500 | 0.6523          | 0.8525   |
| 0.2033        | 2.81  | 138000 | 0.6148          | 0.8562   |
| 0.1923        | 2.82  | 138500 | 0.5841          | 0.8559   |
| 0.1927        | 2.83  | 139000 | 0.6553          | 0.8558   |
| 0.1864        | 2.84  | 139500 | 0.6576          | 0.8554   |
| 0.1959        | 2.85  | 140000 | 0.6552          | 0.8543   |
| 0.1961        | 2.86  | 140500 | 0.6603          | 0.8521   |
| 0.1846        | 2.87  | 141000 | 0.6102          | 0.8607   |
| 0.1887        | 2.88  | 141500 | 0.6500          | 0.8536   |
| 0.1928        | 2.89  | 142000 | 0.6345          | 0.8569   |
| 0.19          | 2.9   | 142500 | 0.6240          | 0.8590   |
| 0.1857        | 2.91  | 143000 | 0.6417          | 0.8555   |
| 0.1879        | 2.92  | 143500 | 0.6619          | 0.8543   |
| 0.1958        | 2.93  | 144000 | 0.6151          | 0.8594   |
| 0.1918        | 2.94  | 144500 | 0.6122          | 0.8571   |
| 0.1828        | 2.95  | 145000 | 0.6402          | 0.8555   |
| 0.1955        | 2.96  | 145500 | 0.6392          | 0.8532   |
| 0.1951        | 2.97  | 146000 | 0.6329          | 0.8556   |
| 0.1812        | 2.98  | 146500 | 0.6222          | 0.8584   |
| 0.1806        | 2.99  | 147000 | 0.6225          | 0.8555   |
| 0.1652        | 3.0   | 147500 | 0.7286          | 0.8562   |
| 0.1463        | 3.01  | 148000 | 0.7288          | 0.8579   |
| 0.1485        | 3.03  | 148500 | 0.7197          | 0.8524   |
| 0.141         | 3.04  | 149000 | 0.7578          | 0.8538   |
| 0.1536        | 3.05  | 149500 | 0.7195          | 0.8570   |
| 0.1433        | 3.06  | 150000 | 0.7697          | 0.8550   |
| 0.1474        | 3.07  | 150500 | 0.7237          | 0.8571   |
| 0.152         | 3.08  | 151000 | 0.7408          | 0.8548   |
| 0.1408        | 3.09  | 151500 | 0.7297          | 0.8585   |
| 0.1153        | 3.1   | 152000 | 0.7630          | 0.8594   |
| 0.1441        | 3.11  | 152500 | 0.7307          | 0.8593   |
| 0.1452        | 3.12  | 153000 | 0.7505          | 0.8551   |
| 0.1397        | 3.13  | 153500 | 0.7455          | 0.8576   |
| 0.1321        | 3.14  | 154000 | 0.7695          | 0.8552   |
| 0.1519        | 3.15  | 154500 | 0.7413          | 0.8563   |
| 0.1436        | 3.16  | 155000 | 0.7371          | 0.8517   |
| 0.1282        | 3.17  | 155500 | 0.7739          | 0.8562   |
| 0.1439        | 3.18  | 156000 | 0.7858          | 0.8521   |
| 0.1309        | 3.19  | 156500 | 0.7487          | 0.8562   |
| 0.1355        | 3.2   | 157000 | 0.7628          | 0.8590   |
| 0.1245        | 3.21  | 157500 | 0.7772          | 0.8551   |
| 0.1313        | 3.22  | 158000 | 0.8121          | 0.8556   |
| 0.1396        | 3.23  | 158500 | 0.7780          | 0.8540   |
| 0.135         | 3.24  | 159000 | 0.8283          | 0.8474   |
| 0.1424        | 3.25  | 159500 | 0.7937          | 0.8530   |
| 0.1344        | 3.26  | 160000 | 0.8198          | 0.8497   |
| 0.1428        | 3.27  | 160500 | 0.7596          | 0.8532   |
| 0.1361        | 3.28  | 161000 | 0.7585          | 0.8556   |
| 0.1451        | 3.29  | 161500 | 0.7733          | 0.8569   |
| 0.1314        | 3.3   | 162000 | 0.7815          | 0.8559   |
| 0.1508        | 3.31  | 162500 | 0.7524          | 0.8529   |
| 0.133         | 3.32  | 163000 | 0.8037          | 0.8554   |
| 0.1562        | 3.33  | 163500 | 0.7041          | 0.8570   |
| 0.1373        | 3.34  | 164000 | 0.7814          | 0.8559   |
| 0.1453        | 3.35  | 164500 | 0.7847          | 0.8545   |
| 0.1493        | 3.36  | 165000 | 0.7332          | 0.8582   |
| 0.1238        | 3.37  | 165500 | 0.7789          | 0.8591   |
| 0.1455        | 3.38  | 166000 | 0.7825          | 0.8537   |
| 0.1437        | 3.39  | 166500 | 0.7808          | 0.8550   |
| 0.1429        | 3.4   | 167000 | 0.7747          | 0.8537   |
| 0.1464        | 3.41  | 167500 | 0.7245          | 0.8567   |
| 0.1303        | 3.42  | 168000 | 0.7983          | 0.8542   |
| 0.14          | 3.43  | 168500 | 0.7847          | 0.8583   |
| 0.1347        | 3.44  | 169000 | 0.7704          | 0.8601   |
| 0.1379        | 3.45  | 169500 | 0.7692          | 0.8572   |
| 0.129         | 3.46  | 170000 | 0.7920          | 0.8558   |
| 0.134         | 3.47  | 170500 | 0.7868          | 0.8549   |
| 0.1395        | 3.48  | 171000 | 0.7483          | 0.8561   |
| 0.1395        | 3.49  | 171500 | 0.7453          | 0.8564   |
| 0.1317        | 3.5   | 172000 | 0.7779          | 0.8566   |
| 0.1405        | 3.51  | 172500 | 0.7883          | 0.8537   |
| 0.1313        | 3.52  | 173000 | 0.7753          | 0.8579   |
| 0.1414        | 3.53  | 173500 | 0.7961          | 0.8530   |
| 0.1439        | 3.54  | 174000 | 0.7842          | 0.8556   |
| 0.1293        | 3.55  | 174500 | 0.7367          | 0.8595   |
| 0.1208        | 3.57  | 175000 | 0.8063          | 0.8558   |
| 0.1399        | 3.58  | 175500 | 0.7805          | 0.8592   |
| 0.1335        | 3.59  | 176000 | 0.7635          | 0.8590   |
| 0.1462        | 3.6   | 176500 | 0.7314          | 0.8569   |
| 0.1299        | 3.61  | 177000 | 0.7712          | 0.8569   |
| 0.1187        | 3.62  | 177500 | 0.7781          | 0.8592   |
| 0.1337        | 3.63  | 178000 | 0.7943          | 0.8559   |
| 0.1353        | 3.64  | 178500 | 0.7611          | 0.8589   |
| 0.1341        | 3.65  | 179000 | 0.7553          | 0.8567   |
| 0.1448        | 3.66  | 179500 | 0.7639          | 0.8554   |
| 0.1223        | 3.67  | 180000 | 0.7942          | 0.8561   |
| 0.1385        | 3.68  | 180500 | 0.7682          | 0.8563   |
| 0.132         | 3.69  | 181000 | 0.7679          | 0.8571   |
| 0.1177        | 3.7   | 181500 | 0.7988          | 0.8553   |
| 0.1313        | 3.71  | 182000 | 0.8045          | 0.8545   |
| 0.1287        | 3.72  | 182500 | 0.7976          | 0.8555   |
| 0.1221        | 3.73  | 183000 | 0.8561          | 0.8528   |
| 0.1373        | 3.74  | 183500 | 0.7870          | 0.8538   |
| 0.1236        | 3.75  | 184000 | 0.8089          | 0.8535   |
| 0.1258        | 3.76  | 184500 | 0.8221          | 0.8549   |
| 0.1358        | 3.77  | 185000 | 0.7897          | 0.8563   |
| 0.1432        | 3.78  | 185500 | 0.7578          | 0.8530   |
| 0.1326        | 3.79  | 186000 | 0.7752          | 0.8557   |
| 0.1286        | 3.8   | 186500 | 0.7791          | 0.8580   |
| 0.1259        | 3.81  | 187000 | 0.7960          | 0.8588   |
| 0.1195        | 3.82  | 187500 | 0.7853          | 0.8572   |
| 0.1332        | 3.83  | 188000 | 0.7800          | 0.8597   |
| 0.1266        | 3.84  | 188500 | 0.7868          | 0.8587   |
| 0.1293        | 3.85  | 189000 | 0.7858          | 0.8578   |
| 0.1165        | 3.86  | 189500 | 0.7846          | 0.8626   |
| 0.12          | 3.87  | 190000 | 0.8114          | 0.8599   |
| 0.1282        | 3.88  | 190500 | 0.7862          | 0.8604   |
| 0.1258        | 3.89  | 191000 | 0.7816          | 0.8584   |
| 0.1329        | 3.9   | 191500 | 0.7855          | 0.8588   |
| 0.1201        | 3.91  | 192000 | 0.8030          | 0.8571   |
| 0.1221        | 3.92  | 192500 | 0.8041          | 0.8587   |
| 0.121         | 3.93  | 193000 | 0.8183          | 0.8570   |
| 0.1205        | 3.94  | 193500 | 0.7720          | 0.8578   |
| 0.1086        | 3.95  | 194000 | 0.8209          | 0.8574   |
| 0.1207        | 3.96  | 194500 | 0.8044          | 0.8576   |
| 0.1097        | 3.97  | 195000 | 0.8197          | 0.8586   |
| 0.1315        | 3.98  | 195500 | 0.7841          | 0.8540   |
| 0.1285        | 3.99  | 196000 | 0.7809          | 0.8579   |
| 0.114         | 4.0   | 196500 | 0.8300          | 0.8555   |
| 0.0815        | 4.01  | 197000 | 0.8590          | 0.8579   |
| 0.0947        | 4.02  | 197500 | 0.8669          | 0.8557   |
| 0.0824        | 4.03  | 198000 | 0.8923          | 0.8549   |
| 0.0967        | 4.04  | 198500 | 0.8733          | 0.8540   |
| 0.074         | 4.05  | 199000 | 0.8776          | 0.8578   |
| 0.0857        | 4.06  | 199500 | 0.8710          | 0.8586   |
| 0.0711        | 4.07  | 200000 | 0.8935          | 0.8581   |
| 0.0838        | 4.08  | 200500 | 0.8909          | 0.8554   |
| 0.0975        | 4.09  | 201000 | 0.8622          | 0.8593   |
| 0.0942        | 4.1   | 201500 | 0.8574          | 0.8592   |
| 0.0814        | 4.12  | 202000 | 0.8987          | 0.8571   |
| 0.0786        | 4.13  | 202500 | 0.8932          | 0.8591   |
| 0.0822        | 4.14  | 203000 | 0.8760          | 0.8597   |
| 0.0852        | 4.15  | 203500 | 0.9043          | 0.8541   |
| 0.0784        | 4.16  | 204000 | 0.8749          | 0.8579   |
| 0.0962        | 4.17  | 204500 | 0.8760          | 0.8566   |
| 0.0929        | 4.18  | 205000 | 0.8875          | 0.8548   |
| 0.0796        | 4.19  | 205500 | 0.8650          | 0.8612   |
| 0.0827        | 4.2   | 206000 | 0.8913          | 0.8598   |
| 0.0865        | 4.21  | 206500 | 0.9193          | 0.8549   |
| 0.0795        | 4.22  | 207000 | 0.9041          | 0.8576   |
| 0.0738        | 4.23  | 207500 | 0.8887          | 0.8594   |
| 0.0977        | 4.24  | 208000 | 0.8578          | 0.8585   |
| 0.0872        | 4.25  | 208500 | 0.8666          | 0.8545   |
| 0.0791        | 4.26  | 209000 | 0.8585          | 0.8608   |
| 0.0761        | 4.27  | 209500 | 0.8992          | 0.8594   |
| 0.0789        | 4.28  | 210000 | 0.8969          | 0.8604   |
| 0.0935        | 4.29  | 210500 | 0.8766          | 0.8588   |
| 0.0837        | 4.3   | 211000 | 0.9028          | 0.8585   |
| 0.0854        | 4.31  | 211500 | 0.8875          | 0.8571   |
| 0.0798        | 4.32  | 212000 | 0.8960          | 0.8567   |
| 0.0797        | 4.33  | 212500 | 0.9093          | 0.8555   |
| 0.0764        | 4.34  | 213000 | 0.8981          | 0.8581   |
| 0.0868        | 4.35  | 213500 | 0.8687          | 0.8603   |
| 0.079         | 4.36  | 214000 | 0.8900          | 0.8583   |
| 0.0767        | 4.37  | 214500 | 0.8849          | 0.8618   |
| 0.0748        | 4.38  | 215000 | 0.9142          | 0.8571   |
| 0.0736        | 4.39  | 215500 | 0.9084          | 0.8579   |
| 0.0688        | 4.4   | 216000 | 0.9309          | 0.8565   |
| 0.0743        | 4.41  | 216500 | 0.9332          | 0.8568   |
| 0.0727        | 4.42  | 217000 | 0.9368          | 0.8586   |
| 0.0862        | 4.43  | 217500 | 0.9165          | 0.8581   |
| 0.0776        | 4.44  | 218000 | 0.9160          | 0.8580   |
| 0.0919        | 4.45  | 218500 | 0.9005          | 0.8563   |
| 0.0919        | 4.46  | 219000 | 0.8861          | 0.8570   |
| 0.0701        | 4.47  | 219500 | 0.8882          | 0.8596   |
| 0.0727        | 4.48  | 220000 | 0.9038          | 0.8592   |
| 0.0847        | 4.49  | 220500 | 0.8863          | 0.8596   |
| 0.075         | 4.5   | 221000 | 0.8946          | 0.8597   |
| 0.0805        | 4.51  | 221500 | 0.9081          | 0.8594   |
| 0.0897        | 4.52  | 222000 | 0.8750          | 0.8589   |
| 0.0825        | 4.53  | 222500 | 0.8962          | 0.8596   |
| 0.0803        | 4.54  | 223000 | 0.8732          | 0.8608   |
| 0.0795        | 4.55  | 223500 | 0.8846          | 0.8590   |
| 0.0775        | 4.56  | 224000 | 0.8976          | 0.8595   |
| 0.0687        | 4.57  | 224500 | 0.9001          | 0.8598   |
| 0.0769        | 4.58  | 225000 | 0.8921          | 0.8596   |
| 0.0707        | 4.59  | 225500 | 0.9036          | 0.8597   |
| 0.08          | 4.6   | 226000 | 0.9301          | 0.8557   |
| 0.076         | 4.61  | 226500 | 0.8969          | 0.8588   |
| 0.0793        | 4.62  | 227000 | 0.8928          | 0.8597   |
| 0.0826        | 4.63  | 227500 | 0.8890          | 0.8580   |
| 0.0893        | 4.64  | 228000 | 0.8843          | 0.8591   |
| 0.0715        | 4.65  | 228500 | 0.9125          | 0.8578   |
| 0.0669        | 4.67  | 229000 | 0.9085          | 0.8591   |
| 0.0724        | 4.68  | 229500 | 0.9056          | 0.8588   |
| 0.0741        | 4.69  | 230000 | 0.9138          | 0.8592   |
| 0.0662        | 4.7   | 230500 | 0.9181          | 0.8587   |
| 0.0703        | 4.71  | 231000 | 0.9096          | 0.8601   |
| 0.0696        | 4.72  | 231500 | 0.8982          | 0.8615   |
| 0.0704        | 4.73  | 232000 | 0.9190          | 0.8597   |
| 0.0754        | 4.74  | 232500 | 0.9082          | 0.8596   |
| 0.0718        | 4.75  | 233000 | 0.8955          | 0.8612   |
| 0.0686        | 4.76  | 233500 | 0.9087          | 0.8606   |
| 0.0647        | 4.77  | 234000 | 0.9036          | 0.8602   |
| 0.071         | 4.78  | 234500 | 0.9109          | 0.8589   |
| 0.0701        | 4.79  | 235000 | 0.9095          | 0.8602   |
| 0.0732        | 4.8   | 235500 | 0.9077          | 0.8601   |
| 0.0626        | 4.81  | 236000 | 0.9172          | 0.8615   |
| 0.083         | 4.82  | 236500 | 0.9144          | 0.8600   |
| 0.0749        | 4.83  | 237000 | 0.9153          | 0.8600   |
| 0.0651        | 4.84  | 237500 | 0.9186          | 0.8598   |
| 0.0609        | 4.85  | 238000 | 0.9195          | 0.8604   |
| 0.0733        | 4.86  | 238500 | 0.9185          | 0.8594   |
| 0.0776        | 4.87  | 239000 | 0.9074          | 0.8599   |
| 0.071         | 4.88  | 239500 | 0.9091          | 0.8596   |
| 0.0724        | 4.89  | 240000 | 0.9041          | 0.8601   |
| 0.0627        | 4.9   | 240500 | 0.9075          | 0.8594   |
| 0.0722        | 4.91  | 241000 | 0.9051          | 0.8604   |
| 0.0629        | 4.92  | 241500 | 0.9043          | 0.8601   |
| 0.0706        | 4.93  | 242000 | 0.9077          | 0.8591   |
| 0.0763        | 4.94  | 242500 | 0.9047          | 0.8593   |
| 0.0785        | 4.95  | 243000 | 0.9006          | 0.8600   |
| 0.0667        | 4.96  | 243500 | 0.9030          | 0.8594   |
| 0.0743        | 4.97  | 244000 | 0.9025          | 0.8594   |
| 0.0775        | 4.98  | 244500 | 0.9024          | 0.8594   |
| 0.0562        | 4.99  | 245000 | 0.9020          | 0.8596   |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.12.1+cu102
- Datasets 2.6.1
- Tokenizers 0.11.6

{"language": ["en"], "license": "mit", "tags": ["generated_from_trainer"], "datasets": ["glue"], "metrics": ["accuracy"], "model-index": [{"name": "roberta-base-mnli-combined-multivalue", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "GLUE MNLI", "type": "glue", "args": "mnli"}, "metrics": [{"type": "accuracy", "value": 0.856946704637917, "name": "Accuracy"}]}]}]}
transformers pytorch tensorboard roberta text-classification generated_from_trainer en dataset:glue license:mit model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #en #dataset-glue #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 

roberta-base-mnli-combined-multivalue
=====================================


This model is a fine-tuned version of roberta-base on the GLUE MNLI dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3918
* Accuracy: 0.8569


Model description
-----------------


More information needed


Intended uses & limitations
---------------------------


More information needed


Training and evaluation data
----------------------------


More information needed


Training procedure
------------------


### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.06
* num\_epochs: 5.0


### Training results



### Framework versions


* Transformers 4.24.0
* Pytorch 1.12.1+cu102
* Datasets 2.6.1
* Tokenizers 0.11.6



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.06
* num\_epochs: 5.0 ### Training results ### Framework versions


* Transformers 4.24.0
* Pytorch 1.12.1+cu102
* Datasets 2.6.1
* Tokenizers 0.11.6
TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #en #dataset-glue #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.06
* num\_epochs: 5.0 ### Training results ### Framework versions


* Transformers 4.24.0
* Pytorch 1.12.1+cu102
* Datasets 2.6.1
* Tokenizers 0.11.6
TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #en #dataset-glue #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.06
* num\_epochs: 5.0### Training results### Framework versions


* Transformers 4.24.0
* Pytorch 1.12.1+cu102
* Datasets 2.6.1
* Tokenizers 0.11.6