Llama3-8B-SETBOX
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: nan
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 100
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0 | 10.0 | 10 | nan |
| 0.0 | 20.0 | 20 | nan |
| 0.0 | 30.0 | 30 | nan |
| 0.0 | 40.0 | 40 | nan |
| 0.0 | 50.0 | 50 | nan |
| 0.0 | 60.0 | 60 | nan |
| 0.0 | 70.0 | 70 | nan |
| 0.0 | 80.0 | 80 | nan |
| 0.0 | 90.0 | 90 | nan |
| 0.0 | 100.0 | 100 | nan |
Framework versions
- PEFT 0.10.0
- Transformers 4.46.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for stlee9048/Llama3-8B-SETBOX
Base model
meta-llama/Meta-Llama-3-8B