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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: AraGPT2-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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# AraGPT2-finetuned-fnd |
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This model is a fine-tuned version of [aubmindlab/aragpt2-mega-detector-long](https://huggingface.co/aubmindlab/aragpt2-mega-detector-long) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5249 |
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- Macro F1: 0.7536 |
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- Accuracy: 0.7626 |
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- Precision: 0.7563 |
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- Recall: 0.7517 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 25 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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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: 5 |
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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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| 0.588 | 1.0 | 798 | 0.5131 | 0.7235 | 0.7384 | 0.7341 | 0.7197 | |
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| 0.462 | 2.0 | 1596 | 0.5112 | 0.7408 | 0.7574 | 0.7587 | 0.7357 | |
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| 0.4034 | 3.0 | 2394 | 0.5249 | 0.7536 | 0.7626 | 0.7563 | 0.7517 | |
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| 0.3234 | 4.0 | 3192 | 0.5967 | 0.7524 | 0.7585 | 0.7516 | 0.7534 | |
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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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