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--- |
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library_name: transformers |
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license: llama3.2 |
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base_model: tanliboy/llama-3.2-3b |
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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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- tanliboy/OpenHermes-2.5-reformat |
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model-index: |
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- name: llama-3.2-3b-sft-2 |
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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-3.2-3b-sft-2 |
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This model is a fine-tuned version of [tanliboy/llama-3.2-3b](https://huggingface.co/tanliboy/llama-3.2-3b) on the tanliboy/OpenHermes-2.5-reformat dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6744 |
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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: 5e-06 |
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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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- num_devices: 8 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 64 |
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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_steps: 1000 |
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- training_steps: 10000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:-----:|:---------------:| |
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| 0.7792 | 0.0673 | 500 | 0.7726 | |
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| 0.7496 | 0.1345 | 1000 | 0.7444 | |
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| 0.7243 | 0.2018 | 1500 | 0.7296 | |
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| 0.7178 | 0.2691 | 2000 | 0.7197 | |
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| 0.7077 | 0.3363 | 2500 | 0.7127 | |
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| 0.6992 | 0.4036 | 3000 | 0.7066 | |
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| 0.6992 | 0.4708 | 3500 | 0.7012 | |
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| 0.6945 | 0.5381 | 4000 | 0.6965 | |
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| 0.6879 | 0.6054 | 4500 | 0.6920 | |
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| 0.6901 | 0.6726 | 5000 | 0.6879 | |
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| 0.6759 | 0.7399 | 5500 | 0.6844 | |
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| 0.6752 | 0.8072 | 6000 | 0.6812 | |
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| 0.6826 | 0.8744 | 6500 | 0.6783 | |
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| 0.6804 | 0.9417 | 7000 | 0.6758 | |
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| 0.6131 | 1.0089 | 7500 | 0.6764 | |
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| 0.6012 | 1.0762 | 8000 | 0.6758 | |
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| 0.6136 | 1.1435 | 8500 | 0.6751 | |
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| 0.6127 | 1.2107 | 9000 | 0.6747 | |
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| 0.6076 | 1.2780 | 9500 | 0.6745 | |
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| 0.6033 | 1.3453 | 10000 | 0.6744 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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