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--- |
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library_name: transformers |
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base_model: csebuetnlp/banglat5 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: banglat5_deed_sum_test_1 |
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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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# banglat5_deed_sum_test_1 |
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This model is a fine-tuned version of [csebuetnlp/banglat5](https://huggingface.co/csebuetnlp/banglat5) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: nan |
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- Rouge1: 0.0 |
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- Rouge2: 0.0 |
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- Rougel: 0.0 |
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- Rougelsum: 0.0 |
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- Gen Len: 0.0 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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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: 5000 |
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- num_epochs: 8 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
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| 0.0 | 0.9973 | 183 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.0 | 2.0 | 367 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.0 | 2.9973 | 550 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.0 | 4.0 | 734 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.0 | 4.9973 | 917 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.0 | 6.0 | 1101 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.0 | 6.9973 | 1284 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.0 | 7.9782 | 1464 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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