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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 |
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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 |
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This model is a fine-tuned version of [yihongLiu/furina](https://huggingface.co/yihongLiu/furina) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0227 |
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- Spearman Corr: 0.7567 |
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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 | 1.61 | 200 | 0.0390 | 0.5403 | |
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| 0.0806 | 3.23 | 400 | 0.0258 | 0.7313 | |
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| 0.0295 | 4.84 | 600 | 0.0231 | 0.7463 | |
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| 0.022 | 6.45 | 800 | 0.0216 | 0.7582 | |
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| 0.017 | 8.06 | 1000 | 0.0241 | 0.7626 | |
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| 0.017 | 9.68 | 1200 | 0.0214 | 0.7723 | |
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| 0.0142 | 11.29 | 1400 | 0.0212 | 0.7660 | |
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| 0.0113 | 12.9 | 1600 | 0.0221 | 0.7655 | |
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| 0.0096 | 14.52 | 1800 | 0.0214 | 0.7690 | |
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| 0.0083 | 16.13 | 2000 | 0.0222 | 0.7595 | |
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| 0.0083 | 17.74 | 2200 | 0.0218 | 0.7649 | |
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| 0.0073 | 19.35 | 2400 | 0.0221 | 0.7600 | |
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| 0.0065 | 20.97 | 2600 | 0.0225 | 0.7606 | |
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| 0.0059 | 22.58 | 2800 | 0.0222 | 0.7574 | |
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| 0.0055 | 24.19 | 3000 | 0.0227 | 0.7567 | |
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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 0.15.1 |
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