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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-2_60-samples_config-3_full
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the GaetanMichelet/chat-60_ft_task-2 dataset. It achieves the following results on the evaluation set:
- Loss: 1.0710
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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 150
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.5659 | 0.8696 | 5 | 1.5846 |
| 1.5947 | 1.9130 | 11 | 1.5811 |
| 1.6305 | 2.9565 | 17 | 1.5758 |
| 1.5682 | 4.0 | 23 | 1.5673 |
| 1.5687 | 4.8696 | 28 | 1.5571 |
| 1.5556 | 5.9130 | 34 | 1.5406 |
| 1.4699 | 6.9565 | 40 | 1.5190 |
| 1.5027 | 8.0 | 46 | 1.4958 |
| 1.5203 | 8.8696 | 51 | 1.4719 |
| 1.4872 | 9.9130 | 57 | 1.4445 |
| 1.4184 | 10.9565 | 63 | 1.4151 |
| 1.3817 | 12.0 | 69 | 1.3868 |
| 1.3397 | 12.8696 | 74 | 1.3648 |
| 1.3234 | 13.9130 | 80 | 1.3390 |
| 1.2893 | 14.9565 | 86 | 1.3122 |
| 1.2999 | 16.0 | 92 | 1.2852 |
| 1.2212 | 16.8696 | 97 | 1.2628 |
| 1.234 | 17.9130 | 103 | 1.2358 |
| 1.1704 | 18.9565 | 109 | 1.2078 |
| 1.1499 | 20.0 | 115 | 1.1796 |
| 1.1265 | 20.8696 | 120 | 1.1570 |
| 1.0716 | 21.9130 | 126 | 1.1357 |
| 1.0332 | 22.9565 | 132 | 1.1223 |
| 1.0631 | 24.0 | 138 | 1.1155 |
| 1.0659 | 24.8696 | 143 | 1.1111 |
| 1.0637 | 25.9130 | 149 | 1.1068 |
| 0.9979 | 26.9565 | 155 | 1.1031 |
| 1.0495 | 28.0 | 161 | 1.0993 |
| 1.0126 | 28.8696 | 166 | 1.0966 |
| 0.9884 | 29.9130 | 172 | 1.0938 |
| 1.0366 | 30.9565 | 178 | 1.0909 |
| 1.0434 | 32.0 | 184 | 1.0886 |
| 1.0222 | 32.8696 | 189 | 1.0862 |
| 0.9978 | 33.9130 | 195 | 1.0842 |
| 0.9593 | 34.9565 | 201 | 1.0824 |
| 1.0383 | 36.0 | 207 | 1.0804 |
| 0.9958 | 36.8696 | 212 | 1.0792 |
| 0.9774 | 37.9130 | 218 | 1.0778 |
| 0.9853 | 38.9565 | 224 | 1.0763 |
| 0.9241 | 40.0 | 230 | 1.0747 |
| 1.0387 | 40.8696 | 235 | 1.0743 |
| 0.9616 | 41.9130 | 241 | 1.0733 |
| 0.9909 | 42.9565 | 247 | 1.0724 |
| 0.9055 | 44.0 | 253 | 1.0720 |
| 1.0025 | 44.8696 | 258 | 1.0722 |
| 0.9325 | 45.9130 | 264 | 1.0711 |
| 0.8921 | 46.9565 | 270 | 1.0723 |
| 0.9079 | 48.0 | 276 | 1.0710 |
| 0.9615 | 48.8696 | 281 | 1.0729 |
| 0.9517 | 49.9130 | 287 | 1.0718 |
| 0.8619 | 50.9565 | 293 | 1.0730 |
| 0.8894 | 52.0 | 299 | 1.0739 |
| 0.8389 | 52.8696 | 304 | 1.0742 |
| 0.9032 | 53.9130 | 310 | 1.0750 |
| 0.9015 | 54.9565 | 316 | 1.0760 |
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-3_full
Base model
meta-llama/Llama-3.1-8B
Finetuned
meta-llama/Llama-3.1-8B-Instruct