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--- |
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base_model: eslamxm/MBart-finetuned-ur-xlsum |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: 1m-model |
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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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# 1m-model |
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This model is a fine-tuned version of [eslamxm/MBart-finetuned-ur-xlsum](https://huggingface.co/eslamxm/MBart-finetuned-ur-xlsum) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5999 |
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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: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 16 |
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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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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.862 | 0.1 | 500 | 0.7994 | |
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| 0.7785 | 0.2 | 1000 | 0.7464 | |
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| 0.7568 | 0.3 | 1500 | 0.7119 | |
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| 0.6927 | 0.4 | 2000 | 0.6837 | |
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| 0.7486 | 0.49 | 2500 | 0.6636 | |
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| 0.7208 | 0.59 | 3000 | 0.6463 | |
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| 0.6784 | 0.69 | 3500 | 0.6297 | |
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| 0.6286 | 0.79 | 4000 | 0.6166 | |
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| 0.6339 | 0.89 | 4500 | 0.6063 | |
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| 0.6738 | 0.99 | 5000 | 0.5999 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.15.0 |
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