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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_auto |
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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_60-samples_config-1_auto |
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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_60-samples_config-1_auto |
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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_auto dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9191 |
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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: 0.0001 |
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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: 8 |
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- total_train_batch_size: 8 |
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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: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-------:|:----:|:---------------:| |
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| 1.1017 | 0.8696 | 5 | 1.1986 | |
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| 1.0551 | 1.9130 | 11 | 1.0321 | |
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| 0.9039 | 2.9565 | 17 | 0.9664 | |
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| 0.8058 | 4.0 | 23 | 0.9391 | |
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| 0.6678 | 4.8696 | 28 | 0.9208 | |
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| 0.5587 | 5.9130 | 34 | 0.9191 | |
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| 0.3836 | 6.9565 | 40 | 1.0232 | |
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| 0.2717 | 8.0 | 46 | 1.2434 | |
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| 0.1582 | 8.8696 | 51 | 1.3662 | |
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| 0.0812 | 9.9130 | 57 | 1.5726 | |
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| 0.0565 | 10.9565 | 63 | 1.7537 | |
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| 0.0417 | 12.0 | 69 | 1.6627 | |
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| 0.0509 | 12.8696 | 74 | 1.6664 | |
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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 |
