BitLlama2-jp-127M-optim-4
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.4021
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=(0.9,0.95) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
6.8073 | 0.07 | 200 | 4.8769 |
4.5389 | 0.15 | 400 | 4.3762 |
4.2297 | 0.22 | 600 | 4.1527 |
4.0242 | 0.29 | 800 | 3.9881 |
3.8902 | 0.36 | 1000 | 3.8885 |
3.7927 | 0.44 | 1200 | 3.8047 |
3.7141 | 0.51 | 1400 | 3.7333 |
3.6597 | 0.58 | 1600 | 3.6681 |
3.579 | 0.66 | 1800 | 3.6041 |
3.5141 | 0.73 | 2000 | 3.5424 |
3.4606 | 0.8 | 2200 | 3.4941 |
3.4116 | 0.88 | 2400 | 3.4467 |
3.361 | 0.95 | 2600 | 3.4021 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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