results
This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.3173
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 3000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.6839 | 0.3997 | 500 | 2.2969 |
| 2.2751 | 0.7994 | 1000 | 2.2539 |
| 2.1746 | 1.1990 | 1500 | 2.2686 |
| 2.0901 | 1.5987 | 2000 | 2.2643 |
| 2.0752 | 1.9984 | 2500 | 2.2541 |
| 1.8984 | 2.3981 | 3000 | 2.3173 |
Framework versions
- PEFT 0.13.1
- Transformers 4.44.2
- Pytorch 2.4.1+cu118
- Datasets 3.0.1
- Tokenizers 0.19.1
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Base model
meta-llama/Llama-2-7b-hf