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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_basic_0.0001
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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_basic_0.0001
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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: 0.0341
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+ - Spearman Corr: 0.7199
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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: 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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+
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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 | 1.59 | 200 | 0.0334 | 0.6305 |
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+ | 0.0623 | 3.19 | 400 | 0.0352 | 0.6918 |
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+ | 0.0245 | 4.78 | 600 | 0.0459 | 0.7114 |
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+ | 0.0165 | 6.37 | 800 | 0.0304 | 0.7227 |
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+ | 0.0118 | 7.97 | 1000 | 0.0333 | 0.7242 |
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+ | 0.0118 | 9.56 | 1200 | 0.0286 | 0.7290 |
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+ | 0.0083 | 11.16 | 1400 | 0.0355 | 0.7148 |
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+ | 0.0063 | 12.75 | 1600 | 0.0382 | 0.7262 |
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+ | 0.0052 | 14.34 | 1800 | 0.0326 | 0.7264 |
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+ | 0.0046 | 15.94 | 2000 | 0.0326 | 0.7237 |
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+ | 0.0046 | 17.53 | 2200 | 0.0347 | 0.7257 |
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+ | 0.0038 | 19.12 | 2400 | 0.0324 | 0.7254 |
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+ | 0.0034 | 20.72 | 2600 | 0.0362 | 0.7210 |
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+ | 0.0031 | 22.31 | 2800 | 0.0341 | 0.7199 |
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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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