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--- |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: myBit-Llama2-jp-127M-4 |
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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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# myBit-Llama2-jp-127M-4 |
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This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.0920 |
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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: 0.0024 |
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- train_batch_size: 96 |
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- eval_batch_size: 96 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: polynomial |
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- lr_scheduler_warmup_steps: 5000 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:------:|:---------------:| |
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| 4.6932 | 0.02 | 2000 | 3.3504 | |
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| 3.252 | 0.03 | 4000 | 3.1987 | |
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| 3.1379 | 0.05 | 6000 | 3.0873 | |
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| 3.0466 | 0.06 | 8000 | 3.0233 | |
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| 2.9925 | 0.08 | 10000 | 2.9819 | |
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| 2.9553 | 0.1 | 12000 | 2.9471 | |
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| 2.9292 | 0.11 | 14000 | 2.9278 | |
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| 2.9158 | 0.13 | 16000 | 2.9159 | |
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| 2.907 | 0.15 | 18000 | 2.9084 | |
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| 2.9018 | 0.16 | 20000 | 2.9015 | |
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| 2.8945 | 0.18 | 22000 | 2.8971 | |
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| 2.8901 | 0.19 | 24000 | 2.9014 | |
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| 2.8906 | 0.21 | 26000 | 2.8980 | |
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| 2.8943 | 0.23 | 28000 | 2.9010 | |
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| 2.8985 | 0.24 | 30000 | 2.9165 | |
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| 3.0191 | 0.26 | 32000 | 3.3484 | |
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| 3.5616 | 0.28 | 34000 | 3.4516 | |
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| 3.2849 | 0.29 | 36000 | 3.0454 | |
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| 3.2425 | 0.31 | 38000 | 3.7183 | |
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| 3.655 | 0.32 | 40000 | 3.8947 | |
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| 3.3151 | 0.34 | 42000 | 3.6150 | |
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| 3.3482 | 0.36 | 44000 | 3.1714 | |
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| 3.1433 | 0.37 | 46000 | 3.1073 | |
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| 3.0462 | 0.39 | 48000 | 2.9786 | |
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| 3.0889 | 0.41 | 50000 | 3.3002 | |
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| 3.4652 | 0.42 | 52000 | 3.3920 | |
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| 3.3726 | 0.44 | 54000 | 3.1293 | |
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| 3.2314 | 0.45 | 56000 | 3.3841 | |
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| 3.5303 | 0.47 | 58000 | 3.3865 | |
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| 3.2828 | 0.49 | 60000 | 3.2591 | |
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| 3.0219 | 0.5 | 62000 | 2.9431 | |
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| 3.0714 | 0.52 | 64000 | 3.2328 | |
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| 3.1354 | 0.54 | 66000 | 3.0794 | |
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| 3.2194 | 0.55 | 68000 | 3.1326 | |
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| 3.394 | 0.57 | 70000 | 3.5974 | |
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| 3.2692 | 0.58 | 72000 | 3.1522 | |
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| 3.1513 | 0.6 | 74000 | 3.1398 | |
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| 3.2473 | 0.62 | 76000 | 3.1921 | |
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| 3.1717 | 0.63 | 78000 | 3.1827 | |
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| 3.211 | 0.65 | 80000 | 3.0845 | |
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| 2.9955 | 0.67 | 82000 | 3.0229 | |
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| 3.3145 | 0.68 | 84000 | 3.3382 | |
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| 3.0703 | 0.7 | 86000 | 3.5395 | |
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| 3.234 | 0.71 | 88000 | 2.9486 | |
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| 3.1077 | 0.73 | 90000 | 2.9488 | |
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| 3.1097 | 0.75 | 92000 | 2.9597 | |
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| 2.8979 | 0.76 | 94000 | 3.0215 | |
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| 3.236 | 0.78 | 96000 | 3.1758 | |
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| 3.1365 | 0.8 | 98000 | 3.4841 | |
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| 3.1954 | 0.81 | 100000 | 2.9520 | |
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| 3.2054 | 0.83 | 102000 | 3.6384 | |
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| 3.2957 | 0.84 | 104000 | 2.9212 | |
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| 2.9358 | 0.86 | 106000 | 3.0166 | |
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| 3.221 | 0.88 | 108000 | 3.3753 | |
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| 3.2241 | 0.89 | 110000 | 3.0858 | |
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| 3.1497 | 0.91 | 112000 | 2.9252 | |
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| 3.198 | 0.93 | 114000 | 3.8514 | |
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| 3.1427 | 0.94 | 116000 | 4.1130 | |
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| 3.2371 | 0.96 | 118000 | 2.8639 | |
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| 3.2576 | 0.97 | 120000 | 2.9192 | |
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| 3.3229 | 0.99 | 122000 | 3.0920 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.15.2 |
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