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--- |
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base_model: yihongLiu/furina |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: furina_seed42_eng_amh_esp_basic_5e-06 |
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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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# furina_seed42_eng_amh_esp_basic_5e-06 |
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This model is a fine-tuned version of [yihongLiu/furina](https://huggingface.co/yihongLiu/furina) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0213 |
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- Spearman Corr: 0.7510 |
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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-06 |
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- train_batch_size: 32 |
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- eval_batch_size: 128 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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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: 30 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Spearman Corr | |
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|:-------------:|:-----:|:----:|:---------------:|:-------------:| |
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| No log | 1.59 | 200 | 0.0439 | 0.1550 | |
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| 0.1335 | 3.17 | 400 | 0.0317 | 0.6373 | |
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| 0.0485 | 4.76 | 600 | 0.0210 | 0.6957 | |
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| 0.0295 | 6.35 | 800 | 0.0249 | 0.7234 | |
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| 0.0295 | 7.94 | 1000 | 0.0196 | 0.7301 | |
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| 0.0243 | 9.52 | 1200 | 0.0195 | 0.7405 | |
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| 0.0221 | 11.11 | 1400 | 0.0214 | 0.7448 | |
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| 0.02 | 12.7 | 1600 | 0.0237 | 0.7426 | |
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| 0.0187 | 14.29 | 1800 | 0.0198 | 0.7470 | |
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| 0.0187 | 15.87 | 2000 | 0.0208 | 0.7501 | |
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| 0.0176 | 17.46 | 2200 | 0.0240 | 0.7495 | |
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| 0.0163 | 19.05 | 2400 | 0.0212 | 0.7518 | |
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| 0.0158 | 20.63 | 2600 | 0.0237 | 0.7475 | |
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| 0.0154 | 22.22 | 2800 | 0.0213 | 0.7510 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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