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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_amh_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_kin_amh_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: 0.0154 |
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- Spearman Corr: 0.8112 |
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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 | 1.95 | 200 | 0.0239 | 0.7162 | |
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| 0.0881 | 3.9 | 400 | 0.0177 | 0.7990 | |
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| 0.0228 | 5.85 | 600 | 0.0167 | 0.8089 | |
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| 0.0168 | 7.8 | 800 | 0.0153 | 0.8124 | |
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| 0.0127 | 9.76 | 1000 | 0.0168 | 0.8121 | |
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| 0.0102 | 11.71 | 1200 | 0.0157 | 0.8114 | |
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| 0.0085 | 13.66 | 1400 | 0.0154 | 0.8122 | |
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| 0.0073 | 15.61 | 1600 | 0.0156 | 0.8132 | |
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| 0.0068 | 17.56 | 1800 | 0.0152 | 0.8097 | |
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| 0.0061 | 19.51 | 2000 | 0.0158 | 0.8094 | |
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| 0.0055 | 21.46 | 2200 | 0.0155 | 0.8098 | |
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| 0.005 | 23.41 | 2400 | 0.0152 | 0.8113 | |
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| 0.005 | 25.37 | 2600 | 0.0152 | 0.8099 | |
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| 0.0046 | 27.32 | 2800 | 0.0153 | 0.8113 | |
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| 0.0044 | 29.27 | 3000 | 0.0154 | 0.8112 | |
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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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