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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_2e-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_2e-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: 0.0162
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- Accuracy: 0.9962
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- F1: 0.9880
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- Precision: 0.9889
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- Recall: 0.9870
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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: 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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| 0.3131 | 1.0 | 666 | 0.2551 | 0.8880 | 0.5518 | 0.7419 | 0.4392 |
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| 0.267 | 2.0 | 1332 | 0.1821 | 0.9280 | 0.7636 | 0.7875 | 0.7410 |
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| 0.2245 | 3.0 | 1998 | 0.0942 | 0.9695 | 0.9034 | 0.8968 | 0.9101 |
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| 0.1135 | 4.0 | 2664 | 0.0514 | 0.9845 | 0.9517 | 0.9339 | 0.9702 |
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| 0.0821 | 5.0 | 3330 | 0.0223 | 0.9944 | 0.9822 | 0.9808 | 0.9837 |
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| 0.0618 | 6.0 | 3996 | 0.0162 | 0.9962 | 0.9880 | 0.9889 | 0.9870 |
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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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