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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_amh_loss_2e-05 |
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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_amh_loss_2e-05 |
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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: 0.0237 |
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- Spearman Corr: 0.7697 |
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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: 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 | 0.9 | 200 | 0.0232 | 0.7664 | |
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| No log | 1.81 | 400 | 0.0228 | 0.7676 | |
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| 0.0039 | 2.71 | 600 | 0.0255 | 0.7675 | |
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| 0.0039 | 3.62 | 800 | 0.0235 | 0.7673 | |
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| 0.0033 | 4.52 | 1000 | 0.0224 | 0.7712 | |
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| 0.0033 | 5.43 | 1200 | 0.0243 | 0.7666 | |
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| 0.0039 | 6.33 | 1400 | 0.0223 | 0.7700 | |
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| 0.0039 | 7.24 | 1600 | 0.0244 | 0.7631 | |
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| 0.0036 | 8.14 | 1800 | 0.0234 | 0.7705 | |
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| 0.0036 | 9.05 | 2000 | 0.0224 | 0.7680 | |
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| 0.0036 | 9.95 | 2200 | 0.0227 | 0.7673 | |
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| 0.0032 | 10.86 | 2400 | 0.0225 | 0.7680 | |
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| 0.0032 | 11.76 | 2600 | 0.0242 | 0.7665 | |
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| 0.0029 | 12.67 | 2800 | 0.0233 | 0.7671 | |
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| 0.0029 | 13.57 | 3000 | 0.0214 | 0.7683 | |
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| 0.0027 | 14.48 | 3200 | 0.0217 | 0.7705 | |
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| 0.0027 | 15.38 | 3400 | 0.0233 | 0.7675 | |
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| 0.0025 | 16.29 | 3600 | 0.0239 | 0.7683 | |
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| 0.0025 | 17.19 | 3800 | 0.0231 | 0.7678 | |
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| 0.0023 | 18.1 | 4000 | 0.0234 | 0.7692 | |
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| 0.0023 | 19.0 | 4200 | 0.0227 | 0.7674 | |
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| 0.0023 | 19.91 | 4400 | 0.0230 | 0.7687 | |
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| 0.0022 | 20.81 | 4600 | 0.0237 | 0.7697 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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