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--- |
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library_name: transformers |
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license: llama3.1 |
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base_model: meta-llama/Llama-3.1-8B |
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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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- trl |
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- sft |
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- generated_from_trainer |
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datasets: |
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- argilla-warehouse/magpie-ultra-v1.0 |
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model-index: |
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- name: Llama-3.1-8B-MagPie-Ultra-500k |
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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-3.1-8B-MagPie-Ultra-500k |
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This model is a fine-tuned version of [meta-llama/Llama-3.1-8B](https://huggingface.co/meta-llama/Llama-3.1-8B) on the argilla-warehouse/magpie-ultra-v1.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5953 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 32 |
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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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.6117 | 0.9998 | 1458 | 0.6077 | |
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| 0.5287 | 1.9997 | 2916 | 0.5882 | |
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| 0.4775 | 2.9995 | 4374 | 0.5953 | |
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### Framework versions |
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- Transformers 4.45.0 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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