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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/SmolLM-135M |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: distily_smollm_dataset_sweep |
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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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# distily_smollm_dataset_sweep |
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This model is a fine-tuned version of [HuggingFaceTB/SmolLM-135M](https://huggingface.co/HuggingFaceTB/SmolLM-135M) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2647 |
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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: 0.0001 |
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- train_batch_size: 8 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: polynomial |
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- lr_scheduler_warmup_ratio: 0.1 |
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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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| No log | 0 | 0 | 18.8388 | |
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| 1.2041 | 0.0401 | 5000 | 1.1584 | |
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| 0.7528 | 0.0802 | 10000 | 0.7396 | |
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| 0.5961 | 0.1202 | 15000 | 0.6070 | |
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| 0.5023 | 0.1603 | 20000 | 0.5307 | |
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| 0.4706 | 0.2004 | 25000 | 0.4836 | |
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| 0.4605 | 0.2405 | 30000 | 0.4512 | |
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| 0.417 | 0.2806 | 35000 | 0.4251 | |
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| 0.4027 | 0.3206 | 40000 | 0.4071 | |
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| 0.3693 | 0.3607 | 45000 | 0.3898 | |
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| 0.3745 | 0.4008 | 50000 | 0.3759 | |
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| 0.3652 | 0.4409 | 55000 | 0.3632 | |
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| 0.3537 | 0.4810 | 60000 | 0.3529 | |
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| 0.3665 | 0.5210 | 65000 | 0.3440 | |
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| 0.3177 | 0.5611 | 70000 | 0.3346 | |
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| 0.3102 | 0.6012 | 75000 | 0.3269 | |
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| 0.3023 | 0.6413 | 80000 | 0.3198 | |
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| 0.3076 | 0.6814 | 85000 | 0.3125 | |
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| 0.3388 | 0.7214 | 90000 | 0.3062 | |
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| 0.298 | 0.7615 | 95000 | 0.3003 | |
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| 0.3052 | 0.8016 | 100000 | 0.2941 | |
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| 0.2678 | 0.8417 | 105000 | 0.2880 | |
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| 0.2684 | 0.8818 | 110000 | 0.2824 | |
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| 0.274 | 0.9218 | 115000 | 0.2764 | |
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| 0.2647 | 0.9619 | 120000 | 0.2706 | |
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### Framework versions |
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- Transformers 4.45.0.dev0 |
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- Pytorch 2.5.0.dev20240910+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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