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--- |
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base_model: meta-llama/Meta-Llama-3-8B |
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library_name: peft |
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license: llama3 |
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tags: |
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- trl |
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- sft |
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- summarization |
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- transformers |
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- llama3 |
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- Lora |
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- QLora |
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- generated_from_trainer |
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model-index: |
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- name: trained_weigths |
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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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# llama3-samsum |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the [Samsumg/samsum](https://huggingface.co/datasets/Samsung/samsum) dataset. |
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## Model description |
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It is a first version and has to be improved. The challenge is to fine-tune the model using limited resources. The fine tuning was performed downsampling the dataset, under Colab free plan restrictions. |
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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: 0.0002 |
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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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 2 |
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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: 0.03 |
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- num_epochs: 1 |
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- mixed_precision_training: Native AMP |
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### Training results |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.43.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
