Llama-3.1-8B_auto
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Llama-31-8B_task-2_60-samples_config-2_auto
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the GaetanMichelet/chat-60_ft_task-2_auto dataset. It achieves the following results on the evaluation set:
- Loss: 0.5986
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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.8574 | 0.6957 | 2 | 0.8904 |
| 0.8746 | 1.7391 | 5 | 0.8490 |
| 0.7842 | 2.7826 | 8 | 0.7717 |
| 0.728 | 3.8261 | 11 | 0.7140 |
| 0.6405 | 4.8696 | 14 | 0.6587 |
| 0.5991 | 5.9130 | 17 | 0.6365 |
| 0.5371 | 6.9565 | 20 | 0.6147 |
| 0.5007 | 8.0 | 23 | 0.6018 |
| 0.4783 | 8.6957 | 25 | 0.5986 |
| 0.4118 | 9.7391 | 28 | 0.6050 |
| 0.4002 | 10.7826 | 31 | 0.6278 |
| 0.3234 | 11.8261 | 34 | 0.6697 |
| 0.2816 | 12.8696 | 37 | 0.7073 |
| 0.2159 | 13.9130 | 40 | 0.7197 |
| 0.1785 | 14.9565 | 43 | 0.7951 |
| 0.1209 | 16.0 | 46 | 0.9001 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for GaetanMichelet/Llama-31-8B_task-2_60-samples_config-2_auto
Base model
meta-llama/Llama-3.1-8B
Finetuned
meta-llama/Llama-3.1-8B-Instruct