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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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- llama-factory |
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- full |
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- generated_from_trainer |
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model-index: |
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- name: llama_8b_lima_43 |
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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_8b_lima_43 |
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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 open_webui_dataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9357 |
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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: 5.5e-06 |
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- train_batch_size: 3 |
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- eval_batch_size: 2 |
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- seed: 66 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 5 |
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- total_train_batch_size: 30 |
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- total_eval_batch_size: 4 |
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- optimizer: Use OptimizerNames.ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: polynomial |
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- lr_scheduler_warmup_steps: 50 |
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- num_epochs: 1.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.0422 | 0.0750 | 80 | 1.0044 | |
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| 0.9127 | 0.1500 | 160 | 0.9607 | |
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| 0.8605 | 0.2251 | 240 | 0.9440 | |
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| 0.9068 | 0.3001 | 320 | 0.9343 | |
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| 0.9147 | 0.3751 | 400 | 0.9293 | |
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| 1.0192 | 0.4501 | 480 | 0.9250 | |
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| 0.8303 | 0.5251 | 560 | 0.9192 | |
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| 1.0284 | 0.6002 | 640 | 0.9292 | |
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| 0.9183 | 0.6752 | 720 | 0.9389 | |
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| 0.9897 | 0.7502 | 800 | 0.9337 | |
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| 1.0209 | 0.8252 | 880 | 0.9390 | |
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| 0.9118 | 0.9002 | 960 | 0.9374 | |
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| 0.9077 | 0.9752 | 1040 | 0.9356 | |
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### Framework versions |
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- Transformers 4.46.1 |
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- Pytorch 2.4.0 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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