generated_from_trainer base_model:google/t5-v1_1-large license:apache-2.0 region:us
---
license: apache-2.0
base_model: google/t5-v1_1-large
tags:
- generated_from_trainer
model-index:
- name: Sentiment-google-t5-v1_1-large-intra_model-dataset-frequency-human_annots_str
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# Sentiment-google-t5-v1_1-large-intra_model-dataset-frequency-human_annots_str

This model is a fine-tuned version of [google/t5-v1_1-large](https://huggingface.co/google/t5-v1_1-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0889

## 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: 0.0001
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 200

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 20.8833       | 1.0   | 44   | 25.4149         |
| 17.9582       | 2.0   | 88   | 15.2004         |
| 12.4496       | 3.0   | 132  | 11.1146         |
| 10.6482       | 4.0   | 176  | 10.7774         |
| 10.0038       | 5.0   | 220  | 10.5784         |
| 9.8548        | 6.0   | 264  | 10.4290         |
| 9.7749        | 7.0   | 308  | 10.2568         |
| 9.4275        | 8.0   | 352  | 9.8102          |
| 8.8894        | 9.0   | 396  | 9.2370          |
| 8.4944        | 10.0  | 440  | 8.9575          |
| 8.4109        | 11.0  | 484  | 8.7954          |
| 8.3217        | 12.0  | 528  | 8.6723          |
| 7.8791        | 13.0  | 572  | 8.5306          |
| 1.0442        | 14.0  | 616  | 0.8718          |
| 0.9076        | 15.0  | 660  | 0.8507          |
| 0.9013        | 16.0  | 704  | 0.8517          |
| 0.9           | 17.0  | 748  | 0.8475          |
| 0.8835        | 18.0  | 792  | 0.8480          |
| 0.8842        | 19.0  | 836  | 0.8525          |
| 0.8836        | 20.0  | 880  | 0.8532          |
| 0.8845        | 21.0  | 924  | 0.8458          |
| 0.8941        | 22.0  | 968  | 0.8485          |
| 0.8819        | 23.0  | 1012 | 0.8450          |
| 0.8921        | 24.0  | 1056 | 0.8513          |
| 0.888         | 25.0  | 1100 | 0.8444          |
| 0.8857        | 26.0  | 1144 | 0.8486          |
| 0.8737        | 27.0  | 1188 | 0.8424          |
| 0.8766        | 28.0  | 1232 | 0.8423          |
| 0.8746        | 29.0  | 1276 | 0.8430          |
| 0.8829        | 30.0  | 1320 | 0.8402          |
| 0.862         | 31.0  | 1364 | 0.8366          |
| 0.8601        | 32.0  | 1408 | 0.8386          |
| 0.8658        | 33.0  | 1452 | 0.8326          |
| 0.8737        | 34.0  | 1496 | 0.8342          |
| 0.8662        | 35.0  | 1540 | 0.8309          |
| 0.8722        | 36.0  | 1584 | 0.8290          |
| 0.8682        | 37.0  | 1628 | 0.8216          |
| 0.859         | 38.0  | 1672 | 0.8430          |
| 0.8554        | 39.0  | 1716 | 0.8170          |
| 0.8565        | 40.0  | 1760 | 0.8114          |
| 0.8402        | 41.0  | 1804 | 0.8079          |
| 0.848         | 42.0  | 1848 | 0.8178          |
| 0.8458        | 43.0  | 1892 | 0.8123          |
| 0.842         | 44.0  | 1936 | 0.8026          |
| 0.8259        | 45.0  | 1980 | 0.7977          |
| 0.8313        | 46.0  | 2024 | 0.7931          |
| 0.8418        | 47.0  | 2068 | 0.7935          |
| 0.8253        | 48.0  | 2112 | 0.7892          |
| 0.8251        | 49.0  | 2156 | 0.7851          |
| 0.8153        | 50.0  | 2200 | 0.7833          |
| 0.809         | 51.0  | 2244 | 0.7822          |
| 0.8137        | 52.0  | 2288 | 0.7759          |
| 0.8152        | 53.0  | 2332 | 0.7781          |
| 0.8201        | 54.0  | 2376 | 0.7812          |
| 0.8049        | 55.0  | 2420 | 0.7795          |
| 0.8003        | 56.0  | 2464 | 0.7730          |
| 0.797         | 57.0  | 2508 | 0.7692          |
| 0.8031        | 58.0  | 2552 | 0.7696          |
| 0.7907        | 59.0  | 2596 | 0.7685          |
| 0.7935        | 60.0  | 2640 | 0.7612          |
| 0.7958        | 61.0  | 2684 | 0.7558          |
| 0.7932        | 62.0  | 2728 | 0.7539          |
| 0.7944        | 63.0  | 2772 | 0.7510          |
| 0.7952        | 64.0  | 2816 | 0.7500          |
| 0.7838        | 65.0  | 2860 | 0.7551          |
| 0.7797        | 66.0  | 2904 | 0.7417          |
| 0.7821        | 67.0  | 2948 | 0.7399          |
| 0.7739        | 68.0  | 2992 | 0.7440          |
| 0.7697        | 69.0  | 3036 | 0.7331          |
| 0.7709        | 70.0  | 3080 | 0.7343          |
| 0.7679        | 71.0  | 3124 | 0.7389          |
| 0.7506        | 72.0  | 3168 | 0.7296          |
| 0.7645        | 73.0  | 3212 | 0.7336          |
| 0.7501        | 74.0  | 3256 | 0.7278          |
| 0.7602        | 75.0  | 3300 | 0.7268          |
| 0.7475        | 76.0  | 3344 | 0.7221          |
| 0.7561        | 77.0  | 3388 | 0.7211          |
| 0.7534        | 78.0  | 3432 | 0.7135          |
| 0.7582        | 79.0  | 3476 | 0.7173          |
| 0.734         | 80.0  | 3520 | 0.7096          |
| 0.7481        | 81.0  | 3564 | 0.7094          |
| 0.7454        | 82.0  | 3608 | 0.7053          |
| 0.7408        | 83.0  | 3652 | 0.6956          |
| 0.7189        | 84.0  | 3696 | 0.6943          |
| 0.7467        | 85.0  | 3740 | 0.6997          |
| 0.7544        | 86.0  | 3784 | 0.7049          |
| 0.7221        | 87.0  | 3828 | 0.6903          |
| 0.7358        | 88.0  | 3872 | 0.6851          |
| 0.727         | 89.0  | 3916 | 0.6807          |
| 0.7127        | 90.0  | 3960 | 0.6828          |
| 0.7158        | 91.0  | 4004 | 0.6837          |
| 0.7284        | 92.0  | 4048 | 0.6818          |
| 0.7153        | 93.0  | 4092 | 0.6906          |
| 0.7172        | 94.0  | 4136 | 0.6804          |
| 0.7076        | 95.0  | 4180 | 0.6694          |
| 0.7009        | 96.0  | 4224 | 0.6722          |
| 0.6915        | 97.0  | 4268 | 0.6775          |
| 0.6997        | 98.0  | 4312 | 0.6596          |
| 0.6924        | 99.0  | 4356 | 0.6595          |
| 0.704         | 100.0 | 4400 | 0.6598          |
| 0.6889        | 101.0 | 4444 | 0.6504          |
| 0.6932        | 102.0 | 4488 | 0.6570          |
| 0.6847        | 103.0 | 4532 | 0.6477          |
| 0.6851        | 104.0 | 4576 | 0.6408          |
| 0.6843        | 105.0 | 4620 | 0.6392          |
| 0.6925        | 106.0 | 4664 | 0.6330          |
| 0.6648        | 107.0 | 4708 | 0.6289          |
| 0.6744        | 108.0 | 4752 | 0.6258          |
| 0.6752        | 109.0 | 4796 | 0.6439          |
| 0.6729        | 110.0 | 4840 | 0.6228          |
| 0.6649        | 111.0 | 4884 | 0.6388          |
| 0.6567        | 112.0 | 4928 | 0.6248          |
| 0.6556        | 113.0 | 4972 | 0.6196          |
| 0.6607        | 114.0 | 5016 | 0.6133          |
| 0.6487        | 115.0 | 5060 | 0.6235          |
| 0.6636        | 116.0 | 5104 | 0.6159          |
| 0.6625        | 117.0 | 5148 | 0.6030          |
| 0.6363        | 118.0 | 5192 | 0.6072          |
| 0.6504        | 119.0 | 5236 | 0.5983          |
| 0.6406        | 120.0 | 5280 | 0.6009          |
| 0.6283        | 121.0 | 5324 | 0.5955          |
| 0.612         | 122.0 | 5368 | 0.5883          |
| 0.6295        | 123.0 | 5412 | 0.5879          |
| 0.6392        | 124.0 | 5456 | 0.5848          |
| 0.6144        | 125.0 | 5500 | 0.5814          |
| 0.6204        | 126.0 | 5544 | 0.5856          |
| 0.6144        | 127.0 | 5588 | 0.5826          |
| 0.6119        | 128.0 | 5632 | 0.5788          |
| 0.6125        | 129.0 | 5676 | 0.5814          |
| 0.6093        | 130.0 | 5720 | 0.5729          |
| 0.6035        | 131.0 | 5764 | 0.5702          |
| 0.6227        | 132.0 | 5808 | 0.5663          |
| 0.6287        | 133.0 | 5852 | 0.5608          |
| 0.6092        | 134.0 | 5896 | 0.5554          |
| 0.6158        | 135.0 | 5940 | 0.5507          |
| 0.6113        | 136.0 | 5984 | 0.5555          |
| 0.5976        | 137.0 | 6028 | 0.5547          |
| 0.595         | 138.0 | 6072 | 0.5436          |
| 0.5891        | 139.0 | 6116 | 0.5417          |
| 0.583         | 140.0 | 6160 | 0.5375          |
| 0.5915        | 141.0 | 6204 | 0.5304          |
| 0.5855        | 142.0 | 6248 | 0.5253          |
| 0.5875        | 143.0 | 6292 | 0.5364          |
| 0.581         | 144.0 | 6336 | 0.5245          |
| 0.5806        | 145.0 | 6380 | 0.5220          |
| 0.5589        | 146.0 | 6424 | 0.5150          |
| 0.573         | 147.0 | 6468 | 0.5252          |
| 0.5843        | 148.0 | 6512 | 0.5169          |
| 0.5705        | 149.0 | 6556 | 0.5156          |
| 0.5756        | 150.0 | 6600 | 0.5208          |
| 0.5575        | 151.0 | 6644 | 0.5028          |
| 0.5574        | 152.0 | 6688 | 0.5049          |
| 0.5598        | 153.0 | 6732 | 0.5054          |
| 0.5571        | 154.0 | 6776 | 0.5096          |
| 0.5673        | 155.0 | 6820 | 0.5012          |
| 0.5634        | 156.0 | 6864 | 0.4902          |
| 0.5601        | 157.0 | 6908 | 0.4949          |
| 0.5423        | 158.0 | 6952 | 0.4851          |
| 0.5568        | 159.0 | 6996 | 0.5020          |
| 0.5664        | 160.0 | 7040 | 0.4846          |
| 0.5523        | 161.0 | 7084 | 0.4865          |
| 0.5502        | 162.0 | 7128 | 0.4797          |
| 0.5374        | 163.0 | 7172 | 0.4735          |
| 0.557         | 164.0 | 7216 | 0.4784          |
| 0.5481        | 165.0 | 7260 | 0.4771          |
| 0.5509        | 166.0 | 7304 | 0.4688          |
| 0.5285        | 167.0 | 7348 | 0.4849          |
| 0.5312        | 168.0 | 7392 | 0.4741          |
| 0.5383        | 169.0 | 7436 | 0.4645          |
| 0.5413        | 170.0 | 7480 | 0.4724          |
| 0.524         | 171.0 | 7524 | 0.4583          |
| 0.5129        | 172.0 | 7568 | 0.4674          |
| 0.5302        | 173.0 | 7612 | 0.4565          |
| 0.5218        | 174.0 | 7656 | 0.4552          |
| 0.5189        | 175.0 | 7700 | 0.4583          |
| 0.5257        | 176.0 | 7744 | 0.4529          |
| 0.5216        | 177.0 | 7788 | 0.4489          |
| 0.5206        | 178.0 | 7832 | 0.4460          |
| 0.5241        | 179.0 | 7876 | 0.4431          |
| 0.5158        | 180.0 | 7920 | 0.4413          |
| 0.509         | 181.0 | 7964 | 0.4492          |
| 0.5111        | 182.0 | 8008 | 0.4431          |
| 0.5174        | 183.0 | 8052 | 0.4382          |
| 0.5122        | 184.0 | 8096 | 0.4305          |
| 0.4983        | 185.0 | 8140 | 0.4346          |
| 0.5022        | 186.0 | 8184 | 0.4358          |
| 0.4951        | 187.0 | 8228 | 0.4357          |
| 0.4989        | 188.0 | 8272 | 0.4325          |
| 0.5096        | 189.0 | 8316 | 0.4291          |
| 0.503         | 190.0 | 8360 | 0.4324          |
| 0.4954        | 191.0 | 8404 | 0.4277          |
| 0.5071        | 192.0 | 8448 | 0.4210          |
| 0.505         | 193.0 | 8492 | 0.4269          |
| 0.5002        | 194.0 | 8536 | 0.4292          |
| 0.5039        | 195.0 | 8580 | 0.4219          |
| 0.5107        | 196.0 | 8624 | 0.4191          |
| 0.5008        | 197.0 | 8668 | 0.4230          |
| 0.5024        | 198.0 | 8712 | 0.4226          |
| 0.4851        | 199.0 | 8756 | 0.4196          |
| 0.5026        | 200.0 | 8800 | 0.4164          |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1
