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--- |
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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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model-index: |
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- name: feedback-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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# feedback-classification |
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This model is a fine-tuned version of [qarib/bert-base-qarib_far_9920k](https://huggingface.co/qarib/bert-base-qarib_far_9920k) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5368 |
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- Macro F1: 0.8354 |
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- Accuracy: 0.8319 |
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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: 2e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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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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- num_epochs: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:| |
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| No log | 1.0 | 341 | 0.5374 | 0.8166 | 0.8099 | |
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| 0.5424 | 2.0 | 682 | 0.5368 | 0.8354 | 0.8319 | |
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### Framework versions |
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- Transformers 4.30.1 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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