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--- |
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library_name: transformers |
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base_model: allenai/scibert_scivocab_uncased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: defect-classification-scibert-baseline-25-epochs |
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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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# defect-classification-scibert-baseline-25-epochs |
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This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2317 |
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- Accuracy: 0.9075 |
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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: 256 |
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- eval_batch_size: 256 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 25 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 1.3655 | 1.0 | 2124 | 1.1784 | 0.8208 | |
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| 0.9439 | 2.0 | 4248 | 0.6611 | 0.8474 | |
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| 0.7364 | 3.0 | 6372 | 0.5215 | 0.8561 | |
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| 0.6355 | 4.0 | 8496 | 0.4250 | 0.8669 | |
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| 0.5592 | 5.0 | 10620 | 0.3694 | 0.8740 | |
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| 0.5411 | 6.0 | 12744 | 0.3482 | 0.8754 | |
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| 0.5056 | 7.0 | 14868 | 0.3418 | 0.8757 | |
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| 0.4838 | 8.0 | 16992 | 0.2492 | 0.9132 | |
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| 0.469 | 9.0 | 19116 | 0.3220 | 0.8785 | |
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| 0.4468 | 10.0 | 21240 | 0.2693 | 0.8964 | |
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| 0.432 | 11.0 | 23364 | 0.2756 | 0.8913 | |
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| 0.4256 | 12.0 | 25488 | 0.2545 | 0.9019 | |
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| 0.4158 | 13.0 | 27612 | 0.2431 | 0.9061 | |
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| 0.3961 | 14.0 | 29736 | 0.2532 | 0.9001 | |
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| 0.3972 | 15.0 | 31860 | 0.2441 | 0.9025 | |
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| 0.3931 | 16.0 | 33984 | 0.2456 | 0.9008 | |
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| 0.3882 | 17.0 | 36108 | 0.2536 | 0.8971 | |
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| 0.3846 | 18.0 | 38232 | 0.2421 | 0.9029 | |
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| 0.3806 | 19.0 | 40356 | 0.2547 | 0.8960 | |
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| 0.3761 | 20.0 | 42480 | 0.2527 | 0.8956 | |
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| 0.3648 | 21.0 | 44604 | 0.2475 | 0.8979 | |
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| 0.3684 | 22.0 | 46728 | 0.2333 | 0.9079 | |
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| 0.3679 | 23.0 | 48852 | 0.2300 | 0.9095 | |
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| 0.3683 | 24.0 | 50976 | 0.2347 | 0.9060 | |
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| 0.3632 | 25.0 | 53100 | 0.2317 | 0.9075 | |
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### Framework versions |
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- Transformers 4.47.0 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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