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--- |
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license: apache-2.0 |
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base_model: Helsinki-NLP/opus-mt-ha-en |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: Baghdad99/saad-opus-ha-to-en |
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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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# Baghdad99/saad-opus-ha-to-en |
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This model is a fine-tuned version of [Helsinki-NLP/opus-mt-ha-en](https://huggingface.co/Helsinki-NLP/opus-mt-ha-en) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 1.9691 |
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- Validation Loss: 3.9168 |
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- Epoch: 24 |
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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': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01} |
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- training_precision: mixed_float16 |
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### Training results |
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| Train Loss | Validation Loss | Epoch | |
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|:----------:|:---------------:|:-----:| |
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| 5.3200 | 4.9969 | 0 | |
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| 4.7301 | 4.7199 | 1 | |
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| 4.3658 | 4.5332 | 2 | |
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| 4.0897 | 4.3940 | 3 | |
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| 3.8568 | 4.2969 | 4 | |
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| 3.6818 | 4.2143 | 5 | |
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| 3.5195 | 4.1530 | 6 | |
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| 3.3799 | 4.1085 | 7 | |
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| 3.2595 | 4.0679 | 8 | |
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| 3.1400 | 4.0438 | 9 | |
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| 3.0337 | 4.0185 | 10 | |
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| 2.9335 | 3.9988 | 11 | |
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| 2.8354 | 3.9766 | 12 | |
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| 2.7461 | 3.9684 | 13 | |
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| 2.6650 | 3.9585 | 14 | |
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| 2.5827 | 3.9477 | 15 | |
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| 2.5062 | 3.9422 | 16 | |
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| 2.4289 | 3.9306 | 17 | |
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| 2.3549 | 3.9208 | 18 | |
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| 2.2882 | 3.9205 | 19 | |
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| 2.2195 | 3.9183 | 20 | |
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| 2.1492 | 3.9157 | 21 | |
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| 2.0888 | 3.9163 | 22 | |
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| 2.0302 | 3.9160 | 23 | |
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| 1.9691 | 3.9168 | 24 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- TensorFlow 2.14.0 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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