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--- |
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license: mit |
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base_model: thenlper/gte-base-zh |
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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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model-index: |
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- name: gte-base-zh-finetuned-emotion |
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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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# gte-base-zh-finetuned-emotion |
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This model is a fine-tuned version of [thenlper/gte-base-zh](https://huggingface.co/thenlper/gte-base-zh) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3958 |
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- Accuracy: 0.8272 |
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- F1: 0.8189 |
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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: 32 |
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- eval_batch_size: 32 |
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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: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 0.4103 | 1.0 | 570 | 0.3675 | 0.8333 | 0.8271 | |
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| 0.3452 | 2.0 | 1140 | 0.3796 | 0.8290 | 0.8180 | |
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| 0.2784 | 3.0 | 1710 | 0.3930 | 0.8397 | 0.8346 | |
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| 0.1904 | 4.0 | 2280 | 0.5113 | 0.8364 | 0.8301 | |
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| 0.1239 | 5.0 | 2850 | 0.6590 | 0.8232 | 0.8100 | |
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| 0.0828 | 6.0 | 3420 | 0.8153 | 0.8254 | 0.8241 | |
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| 0.0624 | 7.0 | 3990 | 0.8672 | 0.8250 | 0.8210 | |
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| 0.0413 | 8.0 | 4560 | 0.9244 | 0.8255 | 0.8159 | |
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| 0.0303 | 9.0 | 5130 | 1.0888 | 0.8199 | 0.8068 | |
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| 0.0233 | 10.0 | 5700 | 1.1171 | 0.8250 | 0.8194 | |
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| 0.0159 | 11.0 | 6270 | 1.2642 | 0.8241 | 0.8115 | |
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| 0.009 | 12.0 | 6840 | 1.2930 | 0.8265 | 0.8169 | |
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| 0.0056 | 13.0 | 7410 | 1.3720 | 0.8260 | 0.8150 | |
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| 0.0019 | 14.0 | 7980 | 1.3878 | 0.8255 | 0.8168 | |
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| 0.003 | 15.0 | 8550 | 1.3958 | 0.8272 | 0.8189 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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