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--- |
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license: mit |
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base_model: Davlan/xlm-roberta-base-finetuned-arabic |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: betteib/xlm-tn-20epochs |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# betteib/xlm-tn-20epochs |
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This model is a fine-tuned version of [Davlan/xlm-roberta-base-finetuned-arabic](https://huggingface.co/Davlan/xlm-roberta-base-finetuned-arabic) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 7.6665 |
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- Train Accuracy: 0.0159 |
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- Validation Loss: 7.4295 |
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- Validation Accuracy: 0.0222 |
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- Epoch: 4 |
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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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- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 0.0001, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0001, 'decay_steps': 18848, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 992, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.001} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch | |
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|:----------:|:--------------:|:---------------:|:-------------------:|:-----:| |
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| 9.7281 | 0.0031 | 9.4281 | 0.0045 | 0 | |
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| 9.2184 | 0.0051 | 8.9814 | 0.0060 | 1 | |
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| 8.7336 | 0.0068 | 8.4005 | 0.0084 | 2 | |
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| 8.1287 | 0.0109 | 7.7969 | 0.0133 | 3 | |
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| 7.6665 | 0.0159 | 7.4295 | 0.0222 | 4 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- TensorFlow 2.12.0 |
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- Datasets 2.19.1 |
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- Tokenizers 0.13.3 |
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