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README.md
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---
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tags:
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- generated_from_trainer
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model-index:
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- name: testc8-1
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# testc8-1
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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.
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It achieves the following results on the evaluation set:
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- Loss: 0.1490
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 64
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- eval_batch_size: 64
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 30
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 0.0415 | 1.0 | 16 | 0.1392 |
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| 0.0443 | 2.0 | 32 | 0.1289 |
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| 0.0471 | 3.0 | 48 | 0.1363 |
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| 0.042 | 4.0 | 64 | 0.1598 |
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| 0.0452 | 5.0 | 80 | 0.1571 |
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| 0.0446 | 6.0 | 96 | 0.1733 |
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| 0.0466 | 7.0 | 112 | 0.1301 |
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| 0.0391 | 8.0 | 128 | 0.1359 |
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| 0.0425 | 9.0 | 144 | 0.1324 |
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| 0.0436 | 10.0 | 160 | 0.0939 |
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| 0.0406 | 11.0 | 176 | 0.1495 |
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| 0.0387 | 12.0 | 192 | 0.1592 |
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| 0.0335 | 13.0 | 208 | 0.1118 |
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| 0.0413 | 14.0 | 224 | 0.1508 |
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| 0.0363 | 15.0 | 240 | 0.1471 |
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| 0.0428 | 16.0 | 256 | 0.1721 |
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| 0.0384 | 17.0 | 272 | 0.1853 |
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| 0.0381 | 18.0 | 288 | 0.1578 |
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| 0.0373 | 19.0 | 304 | 0.1707 |
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| 0.0351 | 20.0 | 320 | 0.1241 |
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| 0.0346 | 21.0 | 336 | 0.1602 |
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| 0.0386 | 22.0 | 352 | 0.1207 |
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| 0.0274 | 23.0 | 368 | 0.1642 |
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| 0.0338 | 24.0 | 384 | 0.1169 |
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| 0.0327 | 25.0 | 400 | 0.1461 |
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| 0.026 | 26.0 | 416 | 0.1323 |
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| 0.0315 | 27.0 | 432 | 0.1403 |
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| 0.042 | 28.0 | 448 | 0.1056 |
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| 0.0346 | 29.0 | 464 | 0.1186 |
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| 0.0294 | 30.0 | 480 | 0.1490 |
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### Framework versions
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- Transformers 4.24.0
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- Pytorch 1.12.1+cu113
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- Datasets 2.7.1
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- Tokenizers 0.13.2
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