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license: apache-2.0 |
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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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base_model: CAMeL-Lab/bert-base-arabic-camelbert-ca |
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model-index: |
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- name: POEMS-CAMELBERT-CA-RUN4 |
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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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# POEMS-CAMELBERT-CA-RUN4 |
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This model is a fine-tuned version of [CAMeL-Lab/bert-base-arabic-camelbert-ca](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-ca) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1498 |
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- Accuracy: 0.5966 |
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- F1: 0.5966 |
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- Precision: 0.5966 |
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- Recall: 0.5966 |
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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: 32 |
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- eval_batch_size: 32 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 1.3444 | 1.0 | 472 | 1.2277 | 0.4552 | 0.4552 | 0.4552 | 0.4552 | |
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| 1.1589 | 2.0 | 944 | 1.0866 | 0.5275 | 0.5275 | 0.5275 | 0.5275 | |
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| 1.0829 | 3.0 | 1416 | 1.1405 | 0.5146 | 0.5146 | 0.5146 | 0.5146 | |
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| 1.0 | 4.0 | 1888 | 1.0262 | 0.5643 | 0.5643 | 0.5643 | 0.5643 | |
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| 0.9288 | 5.0 | 2360 | 1.0574 | 0.5762 | 0.5762 | 0.5762 | 0.5762 | |
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| 0.8776 | 6.0 | 2832 | 1.0456 | 0.5838 | 0.5838 | 0.5838 | 0.5838 | |
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| 0.8166 | 7.0 | 3304 | 1.1421 | 0.5745 | 0.5745 | 0.5745 | 0.5745 | |
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| 0.7636 | 8.0 | 3776 | 1.0959 | 0.5931 | 0.5931 | 0.5931 | 0.5931 | |
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| 0.7173 | 9.0 | 4248 | 1.1400 | 0.5851 | 0.5851 | 0.5851 | 0.5851 | |
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| 0.6915 | 10.0 | 4720 | 1.1498 | 0.5966 | 0.5966 | 0.5966 | 0.5966 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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