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--- |
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license: bigscience-openrail-m |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: Bangla summarization using mt5-base |
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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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# mt5_large_riju_data |
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This model is a fine-tuned version of [MahdiSUST/bn_sum](https://huggingface.co/MahdiSUST/bn_sum) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- eval_loss: 1.3531 |
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- eval_rouge1: {'precision': 41.8541697896367, 'recall': 41.3654041539666, 'fmeasure': 40.98106539607074} |
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- eval_rougeL: {'precision': 39.824364163293794, 'recall': 39.31906760605605, 'fmeasure': 38.97108720823315} |
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- eval_runtime: 229.14 |
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- eval_samples_per_second: 4.159 |
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- eval_steps_per_second: 2.082 |
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- epoch: 9 |
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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: 5.6e-05 |
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- train_batch_size: 9 |
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- eval_batch_size: 9 |
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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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### Framework versions |
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- Transformers 4.27.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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