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--- |
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library_name: transformers |
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license: llama3.2 |
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base_model: NousResearch/Llama-3.2-1B |
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tags: |
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- alignment-handbook |
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- generated_from_trainer |
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datasets: |
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- HuggingFaceH4/ultrachat_200k |
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model-index: |
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- name: llama-3-2-1b-sft |
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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-3-2-1b-sft |
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This model is a fine-tuned version of [NousResearch/Llama-3.2-1B](https://huggingface.co/NousResearch/Llama-3.2-1B) on the HuggingFaceH4/ultrachat_200k dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2759 |
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See the training yaml https://github.com/wassname/SimPO/blob/main/training_configs/llama-3-2-1b-base-sft.yaml |
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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: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 4 |
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- total_train_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: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.3663 | 0.0534 | 200 | 1.3955 | |
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| 1.3413 | 0.1069 | 400 | 1.3722 | |
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| 1.365 | 0.1603 | 600 | 1.3632 | |
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| 1.33 | 0.2138 | 800 | 1.3532 | |
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| 1.3219 | 0.2672 | 1000 | 1.3463 | |
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| 1.3355 | 0.3207 | 1200 | 1.3391 | |
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| 1.334 | 0.3741 | 1400 | 1.3305 | |
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| 1.3183 | 0.4276 | 1600 | 1.3233 | |
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| 1.334 | 0.4810 | 1800 | 1.3161 | |
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| 1.3013 | 0.5345 | 2000 | 1.3087 | |
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| 1.3156 | 0.5879 | 2200 | 1.3016 | |
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| 1.3092 | 0.6414 | 2400 | 1.2953 | |
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| 1.2518 | 0.6948 | 2600 | 1.2895 | |
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| 1.2617 | 0.7483 | 2800 | 1.2846 | |
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| 1.3041 | 0.8017 | 3000 | 1.2809 | |
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| 1.3102 | 0.8552 | 3200 | 1.2781 | |
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| 1.2675 | 0.9086 | 3400 | 1.2765 | |
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| 1.2978 | 0.9621 | 3600 | 1.2759 | |
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### Framework versions |
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- Transformers 4.45.1 |
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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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