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# DIALOGUE

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0320
- Accuracy: 0.9902

## 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2742        | 0.31  | 15   | 1.0896          | 0.7353   |
| 0.9231        | 0.62  | 30   | 0.7436          | 0.8039   |
| 0.7035        | 0.94  | 45   | 0.4280          | 0.9706   |
| 0.4361        | 1.25  | 60   | 0.2308          | 1.0      |
| 0.3081        | 1.56  | 75   | 0.1590          | 0.9902   |
| 0.1794        | 1.88  | 90   | 0.1269          | 0.9706   |
| 0.0988        | 2.19  | 105  | 0.0605          | 0.9902   |
| 0.0606        | 2.5   | 120  | 0.0617          | 0.9902   |
| 0.0372        | 2.81  | 135  | 0.0474          | 0.9902   |
| 0.0209        | 3.12  | 150  | 0.0411          | 0.9902   |
| 0.0134        | 3.44  | 165  | 0.0326          | 0.9902   |
| 0.0099        | 3.75  | 180  | 0.0273          | 0.9902   |
| 0.0085        | 4.06  | 195  | 0.0348          | 0.9902   |
| 0.0065        | 4.38  | 210  | 0.0335          | 0.9902   |
| 0.0058        | 4.69  | 225  | 0.0318          | 0.9902   |
| 0.0047        | 5.0   | 240  | 0.0309          | 0.9902   |
| 0.0041        | 5.31  | 255  | 0.0289          | 0.9902   |
| 0.0041        | 5.62  | 270  | 0.0284          | 0.9902   |
| 0.0038        | 5.94  | 285  | 0.0275          | 0.9902   |
| 0.0036        | 6.25  | 300  | 0.0270          | 0.9902   |
| 0.003         | 6.56  | 315  | 0.0260          | 0.9902   |
| 0.0027        | 6.88  | 330  | 0.0270          | 0.9902   |
| 0.0026        | 7.19  | 345  | 0.0291          | 0.9902   |
| 0.0024        | 7.5   | 360  | 0.0298          | 0.9902   |
| 0.0023        | 7.81  | 375  | 0.0283          | 0.9902   |
| 0.0024        | 8.12  | 390  | 0.0255          | 0.9902   |
| 0.0021        | 8.44  | 405  | 0.0251          | 0.9902   |
| 0.0019        | 8.75  | 420  | 0.0260          | 0.9902   |
| 0.0019        | 9.06  | 435  | 0.0264          | 0.9902   |
| 0.0017        | 9.38  | 450  | 0.0266          | 0.9902   |
| 0.0017        | 9.69  | 465  | 0.0276          | 0.9902   |
| 0.0017        | 10.0  | 480  | 0.0271          | 0.9902   |
| 0.0015        | 10.31 | 495  | 0.0271          | 0.9902   |
| 0.0015        | 10.62 | 510  | 0.0271          | 0.9902   |
| 0.0015        | 10.94 | 525  | 0.0266          | 0.9902   |
| 0.0014        | 11.25 | 540  | 0.0261          | 0.9902   |
| 0.0013        | 11.56 | 555  | 0.0260          | 0.9902   |
| 0.0013        | 11.88 | 570  | 0.0264          | 0.9902   |
| 0.0013        | 12.19 | 585  | 0.0268          | 0.9902   |
| 0.0013        | 12.5  | 600  | 0.0270          | 0.9902   |
| 0.0012        | 12.81 | 615  | 0.0274          | 0.9902   |
| 0.0012        | 13.12 | 630  | 0.0274          | 0.9902   |
| 0.0012        | 13.44 | 645  | 0.0278          | 0.9902   |
| 0.0011        | 13.75 | 660  | 0.0278          | 0.9902   |
| 0.001         | 14.06 | 675  | 0.0278          | 0.9902   |
| 0.001         | 14.38 | 690  | 0.0283          | 0.9902   |
| 0.001         | 14.69 | 705  | 0.0290          | 0.9902   |
| 0.001         | 15.0  | 720  | 0.0286          | 0.9902   |
| 0.001         | 15.31 | 735  | 0.0284          | 0.9902   |
| 0.001         | 15.62 | 750  | 0.0285          | 0.9902   |
| 0.0009        | 15.94 | 765  | 0.0289          | 0.9902   |
| 0.0009        | 16.25 | 780  | 0.0298          | 0.9902   |
| 0.0009        | 16.56 | 795  | 0.0305          | 0.9902   |
| 0.0009        | 16.88 | 810  | 0.0309          | 0.9902   |
| 0.0009        | 17.19 | 825  | 0.0304          | 0.9902   |
| 0.0008        | 17.5  | 840  | 0.0303          | 0.9902   |
| 0.0008        | 17.81 | 855  | 0.0302          | 0.9902   |
| 0.0009        | 18.12 | 870  | 0.0301          | 0.9902   |
| 0.0008        | 18.44 | 885  | 0.0300          | 0.9902   |
| 0.0008        | 18.75 | 900  | 0.0302          | 0.9902   |
| 0.0008        | 19.06 | 915  | 0.0300          | 0.9902   |
| 0.0007        | 19.38 | 930  | 0.0301          | 0.9902   |
| 0.0007        | 19.69 | 945  | 0.0299          | 0.9902   |
| 0.0008        | 20.0  | 960  | 0.0304          | 0.9902   |
| 0.0007        | 20.31 | 975  | 0.0302          | 0.9902   |
| 0.0007        | 20.62 | 990  | 0.0304          | 0.9902   |
| 0.0007        | 20.94 | 1005 | 0.0305          | 0.9902   |
| 0.0007        | 21.25 | 1020 | 0.0312          | 0.9902   |
| 0.0007        | 21.56 | 1035 | 0.0311          | 0.9902   |
| 0.0007        | 21.88 | 1050 | 0.0310          | 0.9902   |
| 0.0007        | 22.19 | 1065 | 0.0310          | 0.9902   |
| 0.0007        | 22.5  | 1080 | 0.0309          | 0.9902   |
| 0.0006        | 22.81 | 1095 | 0.0311          | 0.9902   |
| 0.0006        | 23.12 | 1110 | 0.0313          | 0.9902   |
| 0.0007        | 23.44 | 1125 | 0.0313          | 0.9902   |
| 0.0007        | 23.75 | 1140 | 0.0313          | 0.9902   |
| 0.0006        | 24.06 | 1155 | 0.0312          | 0.9902   |
| 0.0006        | 24.38 | 1170 | 0.0313          | 0.9902   |
| 0.0007        | 24.69 | 1185 | 0.0314          | 0.9902   |
| 0.0006        | 25.0  | 1200 | 0.0313          | 0.9902   |
| 0.0006        | 25.31 | 1215 | 0.0314          | 0.9902   |
| 0.0006        | 25.62 | 1230 | 0.0315          | 0.9902   |
| 0.0006        | 25.94 | 1245 | 0.0316          | 0.9902   |
| 0.0006        | 26.25 | 1260 | 0.0316          | 0.9902   |
| 0.0006        | 26.56 | 1275 | 0.0316          | 0.9902   |
| 0.0006        | 26.88 | 1290 | 0.0316          | 0.9902   |
| 0.0006        | 27.19 | 1305 | 0.0315          | 0.9902   |
| 0.0006        | 27.5  | 1320 | 0.0319          | 0.9902   |
| 0.0006        | 27.81 | 1335 | 0.0320          | 0.9902   |
| 0.0006        | 28.12 | 1350 | 0.0320          | 0.9902   |
| 0.0006        | 28.44 | 1365 | 0.0320          | 0.9902   |
| 0.0006        | 28.75 | 1380 | 0.0320          | 0.9902   |
| 0.0006        | 29.06 | 1395 | 0.0320          | 0.9902   |
| 0.0006        | 29.38 | 1410 | 0.0320          | 0.9902   |
| 0.0006        | 29.69 | 1425 | 0.0320          | 0.9902   |
| 0.0006        | 30.0  | 1440 | 0.0320          | 0.9902   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "bert-base-uncased", "model-index": [{"name": "DIALOGUE", "results": []}]}
transformers tensorboard safetensors bert text-classification generated_from_trainer base_model:bert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us