Configurations choice
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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-3_120-samples_config-2
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the GaetanMichelet/chat-60_ft_task-3 and the GaetanMichelet/chat-120_ft_task-3 datasets. It achieves the following results on the evaluation set:
- Loss: 0.4302
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 |
|---|---|---|---|
| 2.4469 | 0.9091 | 5 | 2.3539 |
| 1.8346 | 2.0 | 11 | 1.4922 |
| 0.7576 | 2.9091 | 16 | 0.7652 |
| 0.6409 | 4.0 | 22 | 0.5627 |
| 0.4304 | 4.9091 | 27 | 0.5238 |
| 0.3624 | 6.0 | 33 | 0.4705 |
| 0.3967 | 6.9091 | 38 | 0.4452 |
| 0.3293 | 8.0 | 44 | 0.4328 |
| 0.2432 | 8.9091 | 49 | 0.4302 |
| 0.2102 | 10.0 | 55 | 0.4359 |
| 0.2004 | 10.9091 | 60 | 0.4583 |
| 0.1634 | 12.0 | 66 | 0.4724 |
| 0.1177 | 12.9091 | 71 | 0.5530 |
| 0.0376 | 14.0 | 77 | 0.7361 |
| 0.0204 | 14.9091 | 82 | 0.7768 |
| 0.0118 | 16.0 | 88 | 0.8608 |
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-3_120-samples_config-2
Base model
meta-llama/Llama-3.1-8B
Finetuned
meta-llama/Llama-3.1-8B-Instruct