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End of training

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README.md ADDED
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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_kin_hau_cross_5e-06
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+ results: []
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+ ---
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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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+
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+ # furina_seed42_eng_kin_hau_cross_5e-06
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+
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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: 0.0271
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+ - Spearman Corr: 0.7253
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Spearman Corr |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------------:|
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+ | No log | 0.53 | 200 | 0.0620 | 0.0297 |
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+ | No log | 1.06 | 400 | 0.0452 | 0.4298 |
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+ | No log | 1.6 | 600 | 0.0368 | 0.5777 |
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+ | 0.0775 | 2.13 | 800 | 0.0330 | 0.6272 |
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+ | 0.0775 | 2.66 | 1000 | 0.0368 | 0.6536 |
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+ | 0.0775 | 3.19 | 1200 | 0.0303 | 0.6597 |
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+ | 0.0775 | 3.72 | 1400 | 0.0300 | 0.6759 |
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+ | 0.0336 | 4.26 | 1600 | 0.0282 | 0.6848 |
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+ | 0.0336 | 4.79 | 1800 | 0.0277 | 0.6941 |
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+ | 0.0336 | 5.32 | 2000 | 0.0269 | 0.7028 |
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+ | 0.0336 | 5.85 | 2200 | 0.0283 | 0.7096 |
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+ | 0.0286 | 6.38 | 2400 | 0.0271 | 0.7074 |
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+ | 0.0286 | 6.91 | 2600 | 0.0271 | 0.7052 |
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+ | 0.0286 | 7.45 | 2800 | 0.0276 | 0.7198 |
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+ | 0.0286 | 7.98 | 3000 | 0.0270 | 0.7159 |
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+ | 0.0252 | 8.51 | 3200 | 0.0277 | 0.7255 |
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+ | 0.0252 | 9.04 | 3400 | 0.0268 | 0.7229 |
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+ | 0.0252 | 9.57 | 3600 | 0.0271 | 0.7253 |
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+
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+
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+ ### Framework versions
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+
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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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