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--- |
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license: mit |
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base_model: roberta-base |
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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: roberta-base_stress_classification |
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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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# roberta-base_stress_classification |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0389 |
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- Accuracy: 0.9938 |
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- F1: 0.9938 |
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- Precision: 0.9938 |
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- Recall: 0.9938 |
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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: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 5 |
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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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| 0.2345 | 1.0 | 160 | 0.1980 | 0.9437 | 0.9437 | 0.9449 | 0.9437 | |
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| 0.2676 | 2.0 | 320 | 0.1086 | 0.9844 | 0.9844 | 0.9848 | 0.9844 | |
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| 0.0393 | 3.0 | 480 | 0.1011 | 0.9812 | 0.9812 | 0.9816 | 0.9812 | |
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| 0.1025 | 4.0 | 640 | 0.0389 | 0.9938 | 0.9938 | 0.9938 | 0.9938 | |
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| 0.0004 | 5.0 | 800 | 0.0654 | 0.9875 | 0.9875 | 0.9876 | 0.9875 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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