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--- |
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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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model-index: |
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- name: scibert_scivocab_uncased-finetuned-molstm-lpm-0.3-25epochs |
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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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# scibert_scivocab_uncased-finetuned-molstm-lpm-0.3-25epochs |
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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: 0.0407 |
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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: 32 |
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- eval_batch_size: 32 |
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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: 25 |
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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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| 0.1073 | 1.0 | 3301 | 0.0633 | |
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| 0.0657 | 2.0 | 6602 | 0.0563 | |
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| 0.059 | 3.0 | 9903 | 0.0536 | |
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| 0.0556 | 4.0 | 13204 | 0.0518 | |
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| 0.0531 | 5.0 | 16505 | 0.0496 | |
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| 0.0511 | 6.0 | 19806 | 0.0489 | |
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| 0.0498 | 7.0 | 23107 | 0.0477 | |
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| 0.0488 | 8.0 | 26408 | 0.0468 | |
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| 0.0478 | 9.0 | 29709 | 0.0464 | |
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| 0.0467 | 10.0 | 33010 | 0.0455 | |
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| 0.0467 | 11.0 | 36311 | 0.0450 | |
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| 0.0458 | 12.0 | 39612 | 0.0454 | |
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| 0.0449 | 13.0 | 42913 | 0.0441 | |
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| 0.0447 | 14.0 | 46214 | 0.0432 | |
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| 0.044 | 15.0 | 49515 | 0.0428 | |
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| 0.0436 | 16.0 | 52816 | 0.0429 | |
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| 0.0433 | 17.0 | 56117 | 0.0428 | |
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| 0.0431 | 18.0 | 59418 | 0.0423 | |
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| 0.0427 | 19.0 | 62719 | 0.0419 | |
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| 0.0425 | 20.0 | 66020 | 0.0420 | |
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| 0.0422 | 21.0 | 69321 | 0.0412 | |
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| 0.0422 | 22.0 | 72622 | 0.0413 | |
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| 0.0416 | 23.0 | 75923 | 0.0407 | |
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| 0.0415 | 24.0 | 79224 | 0.0410 | |
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| 0.0411 | 25.0 | 82525 | 0.0408 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.0.1 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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