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README.md
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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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- f1
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model-index:
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- name: fine_tuned_mix50k_arabert_similarity
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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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# fine_tuned_mix50k_arabert_similarity
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This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5527
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- Accuracy: 0.8802
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- Precision: 0.9022
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- Recall: 0.8227
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- F1: 0.8606
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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: 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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- num_epochs: 10
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| 0.3452 | 1.0 | 9862 | 0.3132 | 0.8737 | 0.8774 | 0.8358 | 0.8561 |
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| 0.2496 | 2.0 | 19724 | 0.2931 | 0.8778 | 0.8678 | 0.8589 | 0.8633 |
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| 0.1939 | 3.0 | 29586 | 0.3597 | 0.8774 | 0.9047 | 0.8128 | 0.8563 |
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| 0.1553 | 4.0 | 39448 | 0.4949 | 0.8788 | 0.8843 | 0.8402 | 0.8617 |
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| 0.1219 | 5.0 | 49310 | 0.5527 | 0.8802 | 0.9022 | 0.8227 | 0.8606 |
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### Framework versions
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- Transformers 4.19.2
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- Pytorch 1.11.0+cu113
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- Datasets 2.2.2
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- Tokenizers 0.12.1
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