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README.md
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---
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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: scibert_claim_id_3e-05
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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_claim_id_3e-05
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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: 0.0071
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- Accuracy: 0.9980
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- F1: 0.9935
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- Precision: 0.9957
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- Recall: 0.9914
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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: 3e-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: 6
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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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| 0.3163 | 1.0 | 666 | 0.2554 | 0.8884 | 0.5534 | 0.7437 | 0.4407 |
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| 0.2673 | 2.0 | 1332 | 0.1671 | 0.9361 | 0.7850 | 0.8309 | 0.7439 |
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| 0.2188 | 3.0 | 1998 | 0.0689 | 0.9769 | 0.9268 | 0.9232 | 0.9303 |
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| 0.0925 | 4.0 | 2664 | 0.0369 | 0.9879 | 0.9624 | 0.9428 | 0.9827 |
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| 0.0635 | 5.0 | 3330 | 0.0109 | 0.9971 | 0.9909 | 0.9928 | 0.9889 |
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| 0.038 | 6.0 | 3996 | 0.0071 | 0.9980 | 0.9935 | 0.9957 | 0.9914 |
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### Framework versions
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- Transformers 4.28.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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