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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-Instruct |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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- accuracy |
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- precision |
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- recall |
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model-index: |
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- name: toxicity-scorer-smollm2-135m-it-freeze |
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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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# toxicity-scorer-smollm2-135m-it-freeze |
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This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-135M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3147 |
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- F1: 0.8264 |
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- Accuracy: 0.8745 |
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- Precision: 0.8384 |
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- Recall: 0.8745 |
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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: 3e-05 |
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- train_batch_size: 44 |
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- eval_batch_size: 44 |
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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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- total_train_batch_size: 352 |
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- total_eval_batch_size: 352 |
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- optimizer: Use OptimizerNames.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: 0.1 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | Precision | Recall | |
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|:-------------:|:------:|:----:|:---------------:|:------:|:--------:|:---------:|:------:| |
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| No log | 0 | 0 | 0.9227 | 0.6386 | 0.5685 | 0.7480 | 0.5685 | |
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| 0.3196 | 1.5596 | 5000 | 0.3147 | 0.8264 | 0.8745 | 0.8384 | 0.8745 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.5.1 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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