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tags: |
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- generated_from_trainer |
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model-index: |
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- name: testc8-2 |
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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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# testc8-2 |
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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: 0.2346 |
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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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| 0.6173 | 1.0 | 16 | 0.3874 | |
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| 0.5383 | 2.0 | 32 | 0.3227 | |
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| 0.4756 | 3.0 | 48 | 0.3142 | |
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| 0.4399 | 4.0 | 64 | 0.3404 | |
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| 0.4462 | 5.0 | 80 | 0.3112 | |
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| 0.4187 | 6.0 | 96 | 0.3185 | |
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| 0.4023 | 7.0 | 112 | 0.2628 | |
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| 0.3712 | 8.0 | 128 | 0.2807 | |
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| 0.3922 | 9.0 | 144 | 0.2516 | |
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| 0.3483 | 10.0 | 160 | 0.1995 | |
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| 0.3417 | 11.0 | 176 | 0.2452 | |
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| 0.3585 | 12.0 | 192 | 0.2236 | |
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| 0.3413 | 13.0 | 208 | 0.2031 | |
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| 0.3452 | 14.0 | 224 | 0.2238 | |
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| 0.317 | 15.0 | 240 | 0.2229 | |
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| 0.3161 | 16.0 | 256 | 0.2591 | |
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| 0.3338 | 17.0 | 272 | 0.2599 | |
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| 0.2949 | 18.0 | 288 | 0.2618 | |
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| 0.3035 | 19.0 | 304 | 0.2436 | |
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| 0.3108 | 20.0 | 320 | 0.2015 | |
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| 0.289 | 21.0 | 336 | 0.2329 | |
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| 0.3144 | 22.0 | 352 | 0.1940 | |
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| 0.2606 | 23.0 | 368 | 0.2334 | |
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| 0.2842 | 24.0 | 384 | 0.1996 | |
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| 0.2892 | 25.0 | 400 | 0.2330 | |
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| 0.2612 | 26.0 | 416 | 0.2163 | |
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| 0.2669 | 27.0 | 432 | 0.2053 | |
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| 0.3147 | 28.0 | 448 | 0.1555 | |
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| 0.286 | 29.0 | 464 | 0.1983 | |
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| 0.2857 | 30.0 | 480 | 0.2346 | |
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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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