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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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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: patentClassfication2 |
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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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# patentClassfication2 |
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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: 0.6329 |
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- Accuracy: 0.6513 |
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- F1: 0.6099 |
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- Precision: 0.6941 |
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- Recall: 0.5438 |
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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: 2.54241e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 41 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- lr_scheduler_warmup_steps: 24 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.635 | 1.0 | 4438 | 0.6329 | 0.6513 | 0.6099 | 0.6941 | 0.5438 | |
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| 0.5772 | 2.0 | 8876 | 0.6393 | 0.6721 | 0.6831 | 0.6624 | 0.7050 | |
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| 0.5355 | 3.0 | 13314 | 0.6558 | 0.6683 | 0.6768 | 0.6613 | 0.6931 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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