shawgpt-ft
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1847
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: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.2637 | 0.9992 | 652 | 1.1808 |
1.142 | 2.0 | 1305 | 1.1452 |
1.0811 | 2.9992 | 1957 | 1.1300 |
1.0268 | 4.0 | 2610 | 1.1262 |
0.9815 | 4.9992 | 3262 | 1.1269 |
0.9389 | 6.0 | 3915 | 1.1323 |
0.9061 | 6.9992 | 4567 | 1.1498 |
0.8749 | 8.0 | 5220 | 1.1575 |
0.8523 | 8.9992 | 5872 | 1.1676 |
0.8351 | 9.9923 | 6520 | 1.1847 |
Framework versions
- PEFT 0.11.1
- Transformers 4.42.3
- Pytorch 2.1.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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