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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: Qwen/Qwen2.5-0.5B |
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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-qwen |
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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-qwen |
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This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B](https://huggingface.co/Qwen/Qwen2.5-0.5B) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1649 |
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- F1: 0.9371 |
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- Accuracy: 0.9380 |
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- Precision: 0.9365 |
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- Recall: 0.9380 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 128 |
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- total_eval_batch_size: 128 |
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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 | 2.2577 | 0.5343 | 0.4464 | 0.7333 | 0.4464 | |
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| 0.1462 | 1.0 | 8816 | 0.1422 | 0.9383 | 0.9400 | 0.9375 | 0.9400 | |
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| 0.1101 | 2.0 | 17632 | 0.1456 | 0.9386 | 0.9399 | 0.9379 | 0.9399 | |
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| 0.0869 | 3.0 | 26448 | 0.1649 | 0.9371 | 0.9380 | 0.9365 | 0.9380 | |
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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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