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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_amh_esp_roman |
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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_amh_esp_roman |
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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: 0.0144 |
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- Spearman Corr: 0.8461 |
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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 | 0.59 | 200 | 0.0299 | 0.6782 | |
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| No log | 1.18 | 400 | 0.0251 | 0.7278 | |
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| No log | 1.76 | 600 | 0.0202 | 0.7493 | |
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| 0.0425 | 2.35 | 800 | 0.0194 | 0.7584 | |
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| 0.0425 | 2.94 | 1000 | 0.0184 | 0.7737 | |
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| 0.0425 | 3.53 | 1200 | 0.0189 | 0.7734 | |
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| 0.0184 | 4.12 | 1400 | 0.0180 | 0.7906 | |
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| 0.0184 | 4.71 | 1600 | 0.0188 | 0.7909 | |
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| 0.0184 | 5.29 | 1800 | 0.0171 | 0.7971 | |
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| 0.0184 | 5.88 | 2000 | 0.0165 | 0.8055 | |
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| 0.0134 | 6.47 | 2200 | 0.0162 | 0.8059 | |
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| 0.0134 | 7.06 | 2400 | 0.0164 | 0.8085 | |
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| 0.0134 | 7.65 | 2600 | 0.0169 | 0.8131 | |
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| 0.0098 | 8.24 | 2800 | 0.0169 | 0.8171 | |
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| 0.0098 | 8.82 | 3000 | 0.0158 | 0.8169 | |
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| 0.0098 | 9.41 | 3200 | 0.0152 | 0.8201 | |
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| 0.0073 | 10.0 | 3400 | 0.0165 | 0.8197 | |
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| 0.0073 | 10.59 | 3600 | 0.0150 | 0.8234 | |
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| 0.0073 | 11.18 | 3800 | 0.0152 | 0.8284 | |
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| 0.0073 | 11.76 | 4000 | 0.0141 | 0.8338 | |
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| 0.0059 | 12.35 | 4200 | 0.0144 | 0.8315 | |
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| 0.0059 | 12.94 | 4400 | 0.0147 | 0.8348 | |
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| 0.0059 | 13.53 | 4600 | 0.0157 | 0.8327 | |
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| 0.0049 | 14.12 | 4800 | 0.0147 | 0.8379 | |
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| 0.0049 | 14.71 | 5000 | 0.0149 | 0.8365 | |
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| 0.0049 | 15.29 | 5200 | 0.0142 | 0.8360 | |
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| 0.0049 | 15.88 | 5400 | 0.0140 | 0.8409 | |
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| 0.0042 | 16.47 | 5600 | 0.0135 | 0.8414 | |
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| 0.0042 | 17.06 | 5800 | 0.0141 | 0.8410 | |
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| 0.0042 | 17.65 | 6000 | 0.0144 | 0.8402 | |
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| 0.0037 | 18.24 | 6200 | 0.0151 | 0.8435 | |
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| 0.0037 | 18.82 | 6400 | 0.0140 | 0.8431 | |
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| 0.0037 | 19.41 | 6600 | 0.0140 | 0.8454 | |
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| 0.0033 | 20.0 | 6800 | 0.0136 | 0.8453 | |
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| 0.0033 | 20.59 | 7000 | 0.0137 | 0.8446 | |
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| 0.0033 | 21.18 | 7200 | 0.0144 | 0.8461 | |
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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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