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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: Assignment2-modified-V4 |
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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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# Assignment2-modified-V4 |
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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: 2.8664 |
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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: 4e-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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 2.5124 | 0.1067 | 200 | 3.1406 | |
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| 2.646 | 0.2133 | 400 | 3.0470 | |
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| 2.4984 | 0.32 | 600 | 2.9933 | |
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| 2.4831 | 0.4267 | 800 | 2.9577 | |
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| 2.4422 | 0.5333 | 1000 | 2.9183 | |
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| 2.3946 | 0.64 | 1200 | 2.8964 | |
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| 2.3091 | 0.7467 | 1400 | 2.8777 | |
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| 2.3445 | 0.8533 | 1600 | 2.8548 | |
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| 2.3067 | 0.96 | 1800 | 2.8339 | |
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| 2.1795 | 1.0667 | 2000 | 2.8570 | |
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| 1.9869 | 1.1733 | 2200 | 2.8557 | |
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| 1.9955 | 1.28 | 2400 | 2.8516 | |
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| 2.0386 | 1.3867 | 2600 | 2.8442 | |
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| 1.9987 | 1.4933 | 2800 | 2.8436 | |
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| 2.0111 | 1.6 | 3000 | 2.8368 | |
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| 1.9452 | 1.7067 | 3200 | 2.8283 | |
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| 1.9509 | 1.8133 | 3400 | 2.8191 | |
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| 1.9163 | 1.92 | 3600 | 2.8148 | |
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| 1.9621 | 2.0267 | 3800 | 2.8338 | |
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| 1.786 | 2.1333 | 4000 | 2.8653 | |
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| 1.7842 | 2.24 | 4200 | 2.8693 | |
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| 1.8084 | 2.3467 | 4400 | 2.8705 | |
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| 1.7057 | 2.4533 | 4600 | 2.8779 | |
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| 1.8589 | 2.56 | 4800 | 2.8660 | |
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| 1.7983 | 2.6667 | 5000 | 2.8655 | |
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| 1.7421 | 2.7733 | 5200 | 2.8659 | |
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| 1.7648 | 2.88 | 5400 | 2.8664 | |
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| 1.8171 | 2.9867 | 5600 | 2.8664 | |
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### Framework versions |
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- Transformers 4.57.1 |
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- Pytorch 2.8.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.22.1 |
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