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LLaMA-Factory badam
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This model is a fine-tuned version of NousResearch/Meta-Llama-3-8B-Instruct on the identity and the iplaw20241002 datasets. It achieves the following results on the evaluation set:
- Loss: 0.1582
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: 1e-05
- 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
- num_epochs: 12.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0713 | 6.8376 | 1000 | 0.1959 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for clinno/iplaw-llama3-8b-Instruct-20241002
Base model
NousResearch/Meta-Llama-3-8B-Instruct