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--- |
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base_model: meta-llama/Meta-Llama-3.1-8B-Instruct |
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datasets: |
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- GaetanMichelet/chat-60_ft_task-1 |
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- GaetanMichelet/chat-120_ft_task-1 |
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- GaetanMichelet/chat-180_ft_task-1 |
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library_name: peft |
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license: llama3.1 |
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tags: |
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- alignment-handbook |
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- trl |
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- sft |
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- generated_from_trainer |
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model-index: |
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- name: Llama-31-8B_task-1_180-samples_config-4 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Llama-31-8B_task-1_180-samples_config-4 |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co./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. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2589 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 150 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-------:|:----:|:---------------:| |
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| 2.0972 | 0.9412 | 8 | 2.0718 | |
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| 2.0234 | 2.0 | 17 | 2.0545 | |
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| 2.0324 | 2.9412 | 25 | 2.0288 | |
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| 2.0064 | 4.0 | 34 | 1.9798 | |
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| 1.9611 | 4.9412 | 42 | 1.9139 | |
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| 1.8283 | 6.0 | 51 | 1.8090 | |
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| 1.6817 | 6.9412 | 59 | 1.7011 | |
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| 1.5762 | 8.0 | 68 | 1.6085 | |
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| 1.5529 | 8.9412 | 76 | 1.5659 | |
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| 1.4817 | 10.0 | 85 | 1.5206 | |
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| 1.5125 | 10.9412 | 93 | 1.4816 | |
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| 1.3226 | 12.0 | 102 | 1.4352 | |
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| 1.3823 | 12.9412 | 110 | 1.3951 | |
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| 1.2564 | 14.0 | 119 | 1.3580 | |
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| 1.1936 | 14.9412 | 127 | 1.3305 | |
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| 1.2322 | 16.0 | 136 | 1.3061 | |
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| 1.1389 | 16.9412 | 144 | 1.2910 | |
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| 1.2119 | 18.0 | 153 | 1.2775 | |
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| 1.0796 | 18.9412 | 161 | 1.2672 | |
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| 1.088 | 20.0 | 170 | 1.2627 | |
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| 1.0344 | 20.9412 | 178 | 1.2631 | |
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| 1.0175 | 22.0 | 187 | 1.2589 | |
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| 0.9509 | 22.9412 | 195 | 1.2707 | |
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| 0.8574 | 24.0 | 204 | 1.2784 | |
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| 0.8673 | 24.9412 | 212 | 1.2985 | |
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| 0.8657 | 26.0 | 221 | 1.3300 | |
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| 0.7453 | 26.9412 | 229 | 1.3725 | |
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| 0.7771 | 28.0 | 238 | 1.3823 | |
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| 0.6941 | 28.9412 | 246 | 1.4508 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.44.0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
