llama-3-8b-hf-ft-chat-lora_1
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 2.9295
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: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.3
- num_epochs: 8
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
3.8283 | 0.9851 | 33 | 3.4186 |
2.711 | 2.0 | 67 | 2.5398 |
2.2647 | 2.9851 | 100 | 2.3353 |
2.0786 | 4.0 | 134 | 2.5266 |
1.9782 | 4.9851 | 167 | 2.9430 |
1.9104 | 6.0 | 201 | 2.9388 |
1.9121 | 6.9851 | 234 | 2.9504 |
1.9022 | 7.8806 | 264 | 2.9295 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
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