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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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- precision |
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- recall |
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model-index: |
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- name: ArBERT-finetuned-fnd |
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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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# ArBERT-finetuned-fnd |
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This model is a fine-tuned version of [UBC-NLP/ARBERT](https://huggingface.co/UBC-NLP/ARBERT) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4956 |
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- Macro F1: 0.7629 |
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- Accuracy: 0.7752 |
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- Precision: 0.7737 |
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- Recall: 0.7584 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 25 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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: 7 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Accuracy | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:| |
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| 0.5033 | 1.0 | 1597 | 0.4831 | 0.7507 | 0.7543 | 0.7495 | 0.7554 | |
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| 0.3858 | 2.0 | 3194 | 0.4956 | 0.7629 | 0.7752 | 0.7737 | 0.7584 | |
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| 0.2675 | 3.0 | 4791 | 0.5964 | 0.7593 | 0.7712 | 0.7685 | 0.7552 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- Pytorch 1.11.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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