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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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- recall |
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- accuracy |
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model-index: |
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- name: Bert-Thesis-NonKFold |
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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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# Bert-Thesis-NonKFold |
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4861 |
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- F1: 0.7464 |
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- Recall: 0.7464 |
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- Accuracy: 0.7464 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Recall | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:| |
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| 1.0891 | 1.0 | 1446 | 0.9053 | 0.7222 | 0.7222 | 0.7222 | |
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| 0.7239 | 2.0 | 2892 | 0.8697 | 0.7397 | 0.7397 | 0.7397 | |
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| 0.4902 | 3.0 | 4338 | 0.8814 | 0.7491 | 0.7491 | 0.7491 | |
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| 0.3287 | 4.0 | 5784 | 0.9655 | 0.7512 | 0.7512 | 0.7512 | |
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| 0.2156 | 5.0 | 7230 | 1.0648 | 0.7450 | 0.7450 | 0.7450 | |
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| 0.1473 | 6.0 | 8676 | 1.1826 | 0.7446 | 0.7446 | 0.7446 | |
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| 0.1071 | 7.0 | 10122 | 1.2922 | 0.7465 | 0.7465 | 0.7465 | |
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| 0.0692 | 8.0 | 11568 | 1.4034 | 0.7483 | 0.7483 | 0.7483 | |
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| 0.0511 | 9.0 | 13014 | 1.4611 | 0.7478 | 0.7478 | 0.7478 | |
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| 0.0386 | 10.0 | 14460 | 1.4861 | 0.7464 | 0.7464 | 0.7464 | |
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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 2.14.5 |
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- Tokenizers 0.13.3 |
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