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--- |
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base_model: nghuyong/ernie-1.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: Ernie-PoliticalBias-Finetune |
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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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# Ernie-PoliticalBias-Finetune |
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This model is a fine-tuned version of [nghuyong/ernie-1.0](https://huggingface.co/nghuyong/ernie-1.0) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4782 |
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- Accuracy: 0.8021 |
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- F1: 0.7908 |
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- Precision: 0.8155 |
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- Recall: 0.7776 |
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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: 5e-05 |
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- train_batch_size: 8 |
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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: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.587 | 1.0 | 3845 | 0.5531 | 0.7607 | 0.7532 | 0.7679 | 0.7454 | |
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| 0.7662 | 2.0 | 7690 | 0.5028 | 0.7948 | 0.7839 | 0.8301 | 0.7626 | |
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| 0.4928 | 3.0 | 11535 | 0.4782 | 0.8021 | 0.7908 | 0.8155 | 0.7776 | |
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| 0.414 | 4.0 | 15380 | 0.5139 | 0.8179 | 0.8043 | 0.8335 | 0.7878 | |
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| 0.2473 | 5.0 | 19225 | 0.5511 | 0.8218 | 0.8103 | 0.8193 | 0.8033 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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