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--- |
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base_model: YituTech/conv-bert-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: conv-bert-base |
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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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# conv-bert-base |
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This model is a fine-tuned version of [YituTech/conv-bert-base](https://huggingface.co/YituTech/conv-bert-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2024 |
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- Precision: 0.7686 |
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- Recall: 0.8278 |
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- F1: 0.7971 |
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- Accuracy: 0.9376 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 3 |
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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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| 0.2235 | 1.0 | 2078 | 0.2225 | 0.7307 | 0.7996 | 0.7636 | 0.9301 | |
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| 0.1814 | 2.0 | 4156 | 0.1946 | 0.7539 | 0.8257 | 0.7881 | 0.9363 | |
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| 0.1469 | 3.0 | 6234 | 0.2024 | 0.7686 | 0.8278 | 0.7971 | 0.9376 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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