sft
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B on the belle_math dataset.
It achieves the following results on the evaluation set:
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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 500
Training results
Training Loss |
Epoch |
Step |
Validation Loss |
0.6272 |
4.4444 |
500 |
0.9967 |
Framework versions
- Transformers 4.43.3
- Pytorch 2.2.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1