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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: distilbert-base-uncased |
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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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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: HW2_finetuned_model |
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results: [] |
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--- |
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language: en |
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license: mit |
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# HW2_finetuned_model |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1321 |
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- Accuracy: 0.97 |
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- F1: 0.9700 |
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- Precision: 0.9717 |
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- Recall: 0.97 |
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## Model description |
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This model wwas used for text classification of the dataset found at huggingface.co/datasets/mrob937/desdep_text_dataset |
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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: 0.0004 |
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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: linear |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.1276 | 1.0 | 120 | 0.2365 | 0.9458 | 0.9457 | 0.9511 | 0.9458 | |
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| 0.4081 | 2.0 | 240 | 0.2115 | 0.9583 | 0.9583 | 0.9615 | 0.9583 | |
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| 0.1085 | 3.0 | 360 | 0.1289 | 0.9708 | 0.9708 | 0.9724 | 0.9708 | |
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### Framework versions |
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- Transformers 4.56.1 |
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- Pytorch 2.8.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.22.0 |
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