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