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--- |
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license: mit |
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base_model: roberta-base |
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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: temp_model_output_dir |
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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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# temp_model_output_dir |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7204 |
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- Precision: 0.8552 |
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- Recall: 0.8448 |
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- F1: 0.8399 |
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- Accuracy: 0.8448 |
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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: 8.8e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: cosine |
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- lr_scheduler_warmup_ratio: 0.2 |
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- num_epochs: 10 |
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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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| 1.209 | 1.0 | 756 | 0.7528 | 0.8238 | 0.8130 | 0.8013 | 0.8130 | |
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| 0.7337 | 2.0 | 1512 | 0.7899 | 0.8209 | 0.8031 | 0.7952 | 0.8031 | |
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| 0.644 | 3.0 | 2268 | 0.7417 | 0.8394 | 0.8299 | 0.8238 | 0.8299 | |
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| 0.4777 | 4.0 | 3024 | 0.7204 | 0.8552 | 0.8448 | 0.8399 | 0.8448 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.15.0 |
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