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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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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: insertion-prop05-ls01 |
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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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# insertion-prop05-ls01 |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2120 |
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- Precision: 0.9800 |
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- Recall: 0.9776 |
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- F1: 0.9788 |
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- Accuracy: 0.9924 |
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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: 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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- num_epochs: 1 |
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- label_smoothing_factor: 0.1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.2462 | 0.32 | 500 | 0.2160 | 0.9754 | 0.9697 | 0.9725 | 0.9902 | |
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| 0.2194 | 0.64 | 1000 | 0.2128 | 0.9784 | 0.9763 | 0.9773 | 0.9919 | |
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| 0.2171 | 0.96 | 1500 | 0.2120 | 0.9800 | 0.9776 | 0.9788 | 0.9924 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.2 |
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