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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- pn_summary |
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metrics: |
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- rouge |
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model-index: |
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- name: mt5-small-persian-dataset |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: pn_summary |
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type: pn_summary |
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config: 1.0.0 |
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split: validation |
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args: 1.0.0 |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 28.6676 |
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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-small-persian-dataset |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the pn_summary dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9495 |
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- Rouge1: 28.6676 |
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- Rouge2: 12.4796 |
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- Rougel: 26.0552 |
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- Rougelsum: 26.0624 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
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| 4.3518 | 1.0 | 1139 | 2.2437 | 24.8632 | 10.0197 | 22.5098 | 22.5578 | |
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| 2.8053 | 2.0 | 2278 | 2.1084 | 26.7746 | 11.2038 | 24.1918 | 24.1592 | |
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| 2.5852 | 3.0 | 3417 | 2.0525 | 27.3138 | 11.6092 | 24.795 | 24.765 | |
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| 2.4537 | 4.0 | 4556 | 2.0333 | 27.8395 | 11.92 | 25.1716 | 25.1786 | |
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| 2.3629 | 5.0 | 5695 | 1.9973 | 28.4229 | 12.2162 | 25.7546 | 25.7399 | |
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| 2.3007 | 6.0 | 6834 | 1.9752 | 28.259 | 12.3229 | 25.6448 | 25.6348 | |
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| 2.2527 | 7.0 | 7973 | 1.9605 | 28.7359 | 12.608 | 26.0384 | 26.0478 | |
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| 2.2227 | 8.0 | 9112 | 1.9571 | 28.5958 | 12.4125 | 25.9516 | 25.9815 | |
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| 2.1983 | 9.0 | 10251 | 1.9557 | 28.5015 | 12.4138 | 25.8887 | 25.8967 | |
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| 2.1769 | 10.0 | 11390 | 1.9495 | 28.6676 | 12.4796 | 26.0552 | 26.0624 | |
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### Framework versions |
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- Transformers 4.26.1 |
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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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