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README.md
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---
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license: apache-2.0
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tags:
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- summarization
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- urdu
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- ur
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- mt5
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- Abstractive Summarization
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- generated_from_trainer
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datasets:
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- xlsum
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model-index:
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- name: mt5-base-finetuned-urdu
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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-base-finetuned-urdu
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This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the xlsum dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.8954
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- Rouge-1: 28.84
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- Rouge-2: 13.87
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- Rouge-l: 25.63
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- Gen Len: 19.0
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- Bertscore: 71.31
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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: 0.0005
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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: 8
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- total_train_batch_size: 32
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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: 5
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- label_smoothing_factor: 0.1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Bertscore |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|
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| 3.6205 | 1.0 | 2114 | 3.0871 | 26.45 | 11.4 | 23.26 | 19.0 | 70.76 |
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| 3.2169 | 2.0 | 4228 | 2.9830 | 27.19 | 11.91 | 23.95 | 19.0 | 70.92 |
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| 3.0787 | 3.0 | 6342 | 2.9284 | 27.9 | 12.57 | 24.62 | 18.99 | 71.13 |
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| 2.9874 | 4.0 | 8456 | 2.9049 | 28.28 | 12.91 | 24.99 | 18.99 | 71.28 |
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| 2.9232 | 5.0 | 10570 | 2.8954 | 28.65 | 13.17 | 25.32 | 18.99 | 71.39 |
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### Framework versions
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- Transformers 4.18.0
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- Pytorch 1.11.0+cu113
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- Datasets 2.1.0
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- Tokenizers 0.12.1
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