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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_esp_hau_basic_0.0001 |
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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_esp_hau_basic_0.0001 |
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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: 0.0312 |
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- Spearman Corr: 0.7194 |
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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: 0.0001 |
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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 | 1.45 | 200 | 0.0282 | 0.6099 | |
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| 0.0652 | 2.91 | 400 | 0.0303 | 0.6702 | |
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| 0.0263 | 4.36 | 600 | 0.0301 | 0.7175 | |
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| 0.0263 | 5.82 | 800 | 0.0333 | 0.7147 | |
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| 0.0178 | 7.27 | 1000 | 0.0346 | 0.7279 | |
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| 0.0123 | 8.73 | 1200 | 0.0274 | 0.7307 | |
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| 0.0089 | 10.18 | 1400 | 0.0290 | 0.7331 | |
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| 0.0089 | 11.64 | 1600 | 0.0302 | 0.7243 | |
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| 0.0064 | 13.09 | 1800 | 0.0292 | 0.7243 | |
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| 0.0052 | 14.55 | 2000 | 0.0297 | 0.7253 | |
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| 0.0044 | 16.0 | 2200 | 0.0335 | 0.7158 | |
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| 0.0044 | 17.45 | 2400 | 0.0313 | 0.7319 | |
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| 0.0038 | 18.91 | 2600 | 0.0289 | 0.7169 | |
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| 0.0032 | 20.36 | 2800 | 0.0312 | 0.7194 | |
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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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