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# bert-base-cased-finetuned-semeval2017-MLM

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4287

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.6571        | 1.0   | 92   | 2.4968          |
| 2.5201        | 2.0   | 184  | 2.3410          |
| 2.3929        | 3.0   | 276  | 2.3291          |
| 2.3975        | 4.0   | 368  | 2.3775          |
| 2.3432        | 5.0   | 460  | 2.3056          |
| 2.2667        | 6.0   | 552  | 2.2628          |
| 2.2044        | 7.0   | 644  | 2.2375          |
| 2.122         | 8.0   | 736  | 2.3169          |
| 2.1331        | 9.0   | 828  | 2.2612          |
| 2.1225        | 10.0  | 920  | 2.2566          |
| 2.0243        | 11.0  | 1012 | 2.2638          |
| 1.9822        | 12.0  | 1104 | 2.2491          |
| 1.9631        | 13.0  | 1196 | 2.1650          |
| 1.9647        | 14.0  | 1288 | 2.2896          |
| 1.9628        | 15.0  | 1380 | 2.2677          |
| 1.8943        | 16.0  | 1472 | 2.2228          |
| 1.8406        | 17.0  | 1564 | 2.2152          |
| 1.8349        | 18.0  | 1656 | 2.1937          |
| 1.7881        | 19.0  | 1748 | 2.2720          |
| 1.8219        | 20.0  | 1840 | 2.2433          |
| 1.762         | 21.0  | 1932 | 2.2314          |
| 1.7639        | 22.0  | 2024 | 2.3166          |
| 1.7431        | 23.0  | 2116 | 2.3272          |
| 1.7016        | 24.0  | 2208 | 2.3099          |
| 1.7155        | 25.0  | 2300 | 2.2311          |
| 1.6764        | 26.0  | 2392 | 2.2315          |
| 1.6664        | 27.0  | 2484 | 2.3288          |
| 1.6264        | 28.0  | 2576 | 2.2736          |
| 1.6485        | 29.0  | 2668 | 2.4059          |
| 1.5953        | 30.0  | 2760 | 2.2846          |
| 1.5861        | 31.0  | 2852 | 2.2768          |
| 1.5561        | 32.0  | 2944 | 2.2790          |
| 1.52          | 33.0  | 3036 | 2.3495          |
| 1.5191        | 34.0  | 3128 | 2.3247          |
| 1.5188        | 35.0  | 3220 | 2.2899          |
| 1.5309        | 36.0  | 3312 | 2.2977          |
| 1.4596        | 37.0  | 3404 | 2.3863          |
| 1.4721        | 38.0  | 3496 | 2.3478          |
| 1.4287        | 39.0  | 3588 | 2.4118          |
| 1.4523        | 40.0  | 3680 | 2.3188          |
| 1.4227        | 41.0  | 3772 | 2.2983          |
| 1.3878        | 42.0  | 3864 | 2.3854          |
| 1.3953        | 43.0  | 3956 | 2.3611          |
| 1.3933        | 44.0  | 4048 | 2.4200          |
| 1.3936        | 45.0  | 4140 | 2.5302          |
| 1.3838        | 46.0  | 4232 | 2.3461          |
| 1.3474        | 47.0  | 4324 | 2.4587          |
| 1.3393        | 48.0  | 4416 | 2.4109          |
| 1.3802        | 49.0  | 4508 | 2.4339          |
| 1.2951        | 50.0  | 4600 | 2.3778          |
| 1.3027        | 51.0  | 4692 | 2.3809          |
| 1.2994        | 52.0  | 4784 | 2.3793          |
| 1.2681        | 53.0  | 4876 | 2.3298          |
| 1.3187        | 54.0  | 4968 | 2.3417          |
| 1.2634        | 55.0  | 5060 | 2.4025          |
| 1.2539        | 56.0  | 5152 | 2.4274          |
| 1.1917        | 57.0  | 5244 | 2.3993          |
| 1.1824        | 58.0  | 5336 | 2.5562          |
| 1.182         | 59.0  | 5428 | 2.4378          |
| 1.1575        | 60.0  | 5520 | 2.4162          |
| 1.1797        | 61.0  | 5612 | 2.4015          |
| 1.2231        | 62.0  | 5704 | 2.3371          |
| 1.2202        | 63.0  | 5796 | 2.3360          |
| 1.1704        | 64.0  | 5888 | 2.4306          |
| 1.1405        | 65.0  | 5980 | 2.3808          |
| 1.1265        | 66.0  | 6072 | 2.4630          |
| 1.1783        | 67.0  | 6164 | 2.4870          |
| 1.089         | 68.0  | 6256 | 2.4710          |
| 1.1336        | 69.0  | 6348 | 2.5672          |
| 1.1555        | 70.0  | 6440 | 2.5471          |
| 1.104         | 71.0  | 6532 | 2.4424          |
| 1.1231        | 72.0  | 6624 | 2.4411          |
| 1.0911        | 73.0  | 6716 | 2.4051          |
| 1.0946        | 74.0  | 6808 | 2.4894          |
| 1.0729        | 75.0  | 6900 | 2.4341          |
| 1.0714        | 76.0  | 6992 | 2.4806          |
| 1.1039        | 77.0  | 7084 | 2.4074          |
| 1.0667        | 78.0  | 7176 | 2.3871          |
| 1.083         | 79.0  | 7268 | 2.5811          |
| 1.0563        | 80.0  | 7360 | 2.4485          |
| 1.0875        | 81.0  | 7452 | 2.4285          |
| 1.0275        | 82.0  | 7544 | 2.5647          |
| 1.0217        | 83.0  | 7636 | 2.5082          |
| 1.0487        | 84.0  | 7728 | 2.5451          |
| 1.0363        | 85.0  | 7820 | 2.4841          |
| 1.0527        | 86.0  | 7912 | 2.5876          |
| 1.0739        | 87.0  | 8004 | 2.4595          |
| 1.0488        | 88.0  | 8096 | 2.5566          |
| 1.0792        | 89.0  | 8188 | 2.3546          |
| 1.0418        | 90.0  | 8280 | 2.4778          |
| 1.0056        | 91.0  | 8372 | 2.4825          |
| 1.0491        | 92.0  | 8464 | 2.4605          |
| 1.009         | 93.0  | 8556 | 2.4413          |
| 1.0           | 94.0  | 8648 | 2.5231          |
| 0.9951        | 95.0  | 8740 | 2.5699          |
| 1.0585        | 96.0  | 8832 | 2.4249          |
| 1.052         | 97.0  | 8924 | 2.5151          |
| 1.0241        | 98.0  | 9016 | 2.4756          |
| 1.014         | 99.0  | 9108 | 2.4787          |
| 1.0623        | 100.0 | 9200 | 2.6042          |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "bert-base-cased-finetuned-semeval2017-MLM", "results": []}]}
transformers pytorch tensorboard bert fill-mask generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

bert-base-cased-finetuned-semeval2017-MLM
=========================================


This model is a fine-tuned version of bert-base-cased on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 2.4287


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: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 100
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 100
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 100
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 100
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2