cls_train_llama3_v1
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 0.6452
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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.7976 | 0.2146 | 50 | 0.8180 |
| 0.7427 | 0.4292 | 100 | 0.7618 |
| 0.7449 | 0.6438 | 150 | 0.7284 |
| 0.6912 | 0.8584 | 200 | 0.6968 |
| 0.5697 | 1.0730 | 250 | 0.6920 |
| 0.5641 | 1.2876 | 300 | 0.6837 |
| 0.5407 | 1.5021 | 350 | 0.6624 |
| 0.5387 | 1.7167 | 400 | 0.6548 |
| 0.5464 | 1.9313 | 450 | 0.6452 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for Sorour/cls_train_llama3_v1
Base model
meta-llama/Meta-Llama-3-8B-Instruct