| | --- |
| | tags: |
| | - generated_from_trainer |
| | base_model: shafin/chemical-bert-uncased-finetuned-cust-c2 |
| | model-index: |
| | - name: testc8-1 |
| | 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. --> |
| |
|
| | # testc8-1 |
| |
|
| | This model is a fine-tuned version of [shafin/chemical-bert-uncased-finetuned-cust-c2](https://huggingface.co/shafin/chemical-bert-uncased-finetuned-cust-c2) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.1490 |
| |
|
| | ## 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: 64 |
| | - eval_batch_size: 64 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 30 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:-----:|:----:|:---------------:| |
| | | 0.0415 | 1.0 | 16 | 0.1392 | |
| | | 0.0443 | 2.0 | 32 | 0.1289 | |
| | | 0.0471 | 3.0 | 48 | 0.1363 | |
| | | 0.042 | 4.0 | 64 | 0.1598 | |
| | | 0.0452 | 5.0 | 80 | 0.1571 | |
| | | 0.0446 | 6.0 | 96 | 0.1733 | |
| | | 0.0466 | 7.0 | 112 | 0.1301 | |
| | | 0.0391 | 8.0 | 128 | 0.1359 | |
| | | 0.0425 | 9.0 | 144 | 0.1324 | |
| | | 0.0436 | 10.0 | 160 | 0.0939 | |
| | | 0.0406 | 11.0 | 176 | 0.1495 | |
| | | 0.0387 | 12.0 | 192 | 0.1592 | |
| | | 0.0335 | 13.0 | 208 | 0.1118 | |
| | | 0.0413 | 14.0 | 224 | 0.1508 | |
| | | 0.0363 | 15.0 | 240 | 0.1471 | |
| | | 0.0428 | 16.0 | 256 | 0.1721 | |
| | | 0.0384 | 17.0 | 272 | 0.1853 | |
| | | 0.0381 | 18.0 | 288 | 0.1578 | |
| | | 0.0373 | 19.0 | 304 | 0.1707 | |
| | | 0.0351 | 20.0 | 320 | 0.1241 | |
| | | 0.0346 | 21.0 | 336 | 0.1602 | |
| | | 0.0386 | 22.0 | 352 | 0.1207 | |
| | | 0.0274 | 23.0 | 368 | 0.1642 | |
| | | 0.0338 | 24.0 | 384 | 0.1169 | |
| | | 0.0327 | 25.0 | 400 | 0.1461 | |
| | | 0.026 | 26.0 | 416 | 0.1323 | |
| | | 0.0315 | 27.0 | 432 | 0.1403 | |
| | | 0.042 | 28.0 | 448 | 0.1056 | |
| | | 0.0346 | 29.0 | 464 | 0.1186 | |
| | | 0.0294 | 30.0 | 480 | 0.1490 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.24.0 |
| | - Pytorch 1.12.1+cu113 |
| | - Datasets 2.7.1 |
| | - Tokenizers 0.13.2 |
| |
|
