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--- |
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base_model: bert-base-chinese |
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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: berttest2 |
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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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# berttest2 |
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This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert-base-chinese) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0206 |
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- Precision: 0.9610 |
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- Recall: 0.9653 |
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- F1: 0.9631 |
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- Accuracy: 0.9956 |
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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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| 0.028 | 1.0 | 2609 | 0.0225 | 0.9385 | 0.9350 | 0.9368 | 0.9932 | |
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| 0.011 | 2.0 | 5218 | 0.0182 | 0.9542 | 0.9592 | 0.9567 | 0.9951 | |
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| 0.0044 | 3.0 | 7827 | 0.0206 | 0.9610 | 0.9653 | 0.9631 | 0.9956 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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