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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: HuggingFaceTB/SmolLM2-1.7B |
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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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model-index: |
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- name: HuggingFaceTB/SmolLM2-1.7B |
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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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# HuggingFaceTB/SmolLM2-1.7B |
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This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-1.7B](https://huggingface.co/HuggingFaceTB/SmolLM2-1.7B) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2902 |
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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: 4 |
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- total_train_batch_size: 256 |
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- total_eval_batch_size: 64 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.05 |
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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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| 1.3939 | 0.2463 | 200 | 1.3921 | |
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| 1.2806 | 0.4926 | 400 | 1.3156 | |
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| 1.2827 | 0.7389 | 600 | 1.2938 | |
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| 1.2807 | 0.9852 | 800 | 1.2902 | |
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### Framework versions |
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- Transformers 4.48.3 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.21.0 |
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