| --- |
| base_model: nghuyong/ernie-2.0-base-en |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: ernie-2.0-base-en |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # ernie-2.0-base-en |
|
|
| This model is a fine-tuned version of [nghuyong/ernie-2.0-base-en](https://huggingface.co/nghuyong/ernie-2.0-base-en) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2022 |
| - Precision: 0.7745 |
| - Recall: 0.8255 |
| - F1: 0.7992 |
| - Accuracy: 0.9392 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 2e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 3 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | 0.2221 | 1.0 | 2078 | 0.2066 | 0.7130 | 0.8024 | 0.7551 | 0.9309 | |
| | 0.1813 | 2.0 | 4156 | 0.1972 | 0.7573 | 0.8224 | 0.7885 | 0.9362 | |
| | 0.1397 | 3.0 | 6234 | 0.2022 | 0.7745 | 0.8255 | 0.7992 | 0.9392 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.35.2 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.16.1 |
| - Tokenizers 0.15.1 |
|
|
