Configurations choice
Collection
Choice of configuration based on the results of different fine-tuning. All provide mor or less same results but 1 and 2 are way faster! (lr)
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Llama-31-8B_task-1_180-samples_config-2_full
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the GaetanMichelet/chat-60_ft_task-1, the GaetanMichelet/chat-120_ft_task-1 and the GaetanMichelet/chat-180_ft_task-1 datasets. It achieves the following results on the evaluation set:
- Loss: 0.8726
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 |
|---|---|---|---|
| 2.375 | 0.9412 | 8 | 2.2872 |
| 1.9761 | 2.0 | 17 | 1.8512 |
| 1.5652 | 2.9412 | 25 | 1.3759 |
| 1.0274 | 4.0 | 34 | 1.0474 |
| 0.9811 | 4.9412 | 42 | 0.9874 |
| 0.9464 | 6.0 | 51 | 0.9454 |
| 0.8491 | 6.9412 | 59 | 0.9103 |
| 0.8043 | 8.0 | 68 | 0.8866 |
| 0.7279 | 8.9412 | 76 | 0.8726 |
| 0.6704 | 10.0 | 85 | 0.8894 |
| 0.6154 | 10.9412 | 93 | 0.9156 |
| 0.4469 | 12.0 | 102 | 0.9677 |
| 0.3873 | 12.9412 | 110 | 1.0959 |
| 0.3086 | 14.0 | 119 | 1.2353 |
| 0.1952 | 14.9412 | 127 | 1.3687 |
| 0.1665 | 16.0 | 136 | 1.4523 |
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-1_180-samples_config-2_full
Base model
meta-llama/Llama-3.1-8B
Finetuned
meta-llama/Llama-3.1-8B-Instruct