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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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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: SciBERT_25K_steps_bs64 |
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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_25K_steps_bs64 |
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This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0177 |
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- Accuracy: 0.9941 |
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- Precision: 0.7990 |
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- Recall: 0.5288 |
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- F1: 0.6364 |
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- Hamming: 0.0059 |
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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: 1e-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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- lr_scheduler_warmup_ratio: 0.1 |
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- training_steps: 25000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Hamming | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:| |
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| 0.0467 | 0.16 | 5000 | 0.0416 | 0.9902 | 0.0 | 0.0 | 0.0 | 0.0098 | |
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| 0.0236 | 0.32 | 10000 | 0.0223 | 0.9932 | 0.8192 | 0.3929 | 0.5311 | 0.0068 | |
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| 0.0198 | 0.47 | 15000 | 0.0190 | 0.9939 | 0.8015 | 0.4934 | 0.6108 | 0.0061 | |
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| 0.0185 | 0.63 | 20000 | 0.0180 | 0.9940 | 0.7974 | 0.5220 | 0.6310 | 0.0060 | |
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| 0.0181 | 0.79 | 25000 | 0.0177 | 0.9941 | 0.7990 | 0.5288 | 0.6364 | 0.0059 | |
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### Framework versions |
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- Transformers 4.35.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.7.1 |
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- Tokenizers 0.14.1 |
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