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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/SmolLM2-135M |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: chennus-2-70m |
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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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# chennus-2-70m |
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This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-135M](https://huggingface.co/HuggingFaceTB/SmolLM2-135M) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8759 |
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- Accuracy: 0.0077 |
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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-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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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:--------:| |
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| 1.0256 | 0.1616 | 200 | 1.0056 | 0.0079 | |
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| 0.9819 | 0.3231 | 400 | 0.9644 | 0.0078 | |
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| 0.9504 | 0.4847 | 600 | 0.9461 | 0.0077 | |
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| 0.9296 | 0.6462 | 800 | 0.9290 | 0.0078 | |
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| 0.9113 | 0.8078 | 1000 | 0.9182 | 0.0077 | |
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| 0.9121 | 0.9693 | 1200 | 0.9096 | 0.0077 | |
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| 0.9027 | 1.1309 | 1400 | 0.9026 | 0.0077 | |
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| 0.8894 | 1.2924 | 1600 | 0.8971 | 0.0077 | |
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| 0.8934 | 1.4540 | 1800 | 0.8924 | 0.0077 | |
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| 0.8839 | 1.6155 | 2000 | 0.8876 | 0.0077 | |
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| 0.8935 | 1.7771 | 2200 | 0.8843 | 0.0077 | |
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| 0.8847 | 1.9386 | 2400 | 0.8836 | 0.0077 | |
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| 0.8749 | 2.1002 | 2600 | 0.8819 | 0.0077 | |
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| 0.8817 | 2.2617 | 2800 | 0.8807 | 0.0077 | |
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| 0.8712 | 2.4233 | 3000 | 0.8787 | 0.0077 | |
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| 0.8768 | 2.5848 | 3200 | 0.8775 | 0.0077 | |
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| 0.8726 | 2.7464 | 3400 | 0.8772 | 0.0077 | |
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| 0.8789 | 2.9079 | 3600 | 0.8763 | 0.0077 | |
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| 0.8782 | 3.0695 | 3800 | 0.8765 | 0.0077 | |
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| 0.8724 | 3.2310 | 4000 | 0.8763 | 0.0077 | |
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| 0.8812 | 3.3926 | 4200 | 0.8767 | 0.0077 | |
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| 0.8727 | 3.5541 | 4400 | 0.8762 | 0.0077 | |
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| 0.8730 | 3.7157 | 4600 | 0.8767 | 0.0077 | |
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| 0.8694 | 3.8772 | 4800 | 0.8763 | 0.0077 | |
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| 0.8689 | 4.0388 | 5000 | 0.8760 | 0.0077 | |
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| 0.8791 | 4.2003 | 5200 | 0.8764 | 0.0077 | |
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| 0.8788 | 4.3619 | 5400 | 0.8764 | 0.0077 | |
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| 0.8717 | 4.5234 | 5600 | 0.8763 | 0.0077 | |
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| 0.8797 | 4.6850 | 5800 | 0.8761 | 0.0077 | |
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| 0.8744 | 4.8465 | 6000 | 0.8759 | 0.0077 | |
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### Framework versions |
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- Transformers 5.0.0 |
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- Pytorch 2.9.0+cu128 |
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- Datasets 4.0.0 |
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- Tokenizers 0.22.2 |
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