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--- |
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license: apache-2.0 |
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base_model: google/mt5-small |
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tags: |
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- summarization |
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- T2SAM |
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- abstractive summarization |
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metrics: |
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- rouge |
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model-index: |
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- name: mt5-small-finetuned-inshorts-news-summary |
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results: [] |
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language: |
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- en |
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library_name: transformers |
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datasets: |
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- sandeep16064/news_summary |
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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-finetuned-inshorts-news-summary |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the [inshorts-news-summary dataset] (https://huggingface.co/datasets/sandeep16064/news_summary). |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5399 |
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- Rouge1: 54.613 |
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- Rouge2: 31.1543 |
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- Rougel: 50.7709 |
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- Rougelsum: 50.7907 |
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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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| 3.3244 | 1.0 | 5511 | 1.8904 | 51.0778 | 28.3112 | 47.4136 | 47.404 | |
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| 2.2747 | 2.0 | 11022 | 1.7450 | 51.8372 | 28.9814 | 48.0917 | 48.0965 | |
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| 2.0745 | 3.0 | 16533 | 1.6567 | 52.518 | 29.7276 | 48.727 | 48.7504 | |
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| 1.9516 | 4.0 | 22044 | 1.6210 | 54.2404 | 30.8927 | 50.4042 | 50.3996 | |
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| 1.8714 | 5.0 | 27555 | 1.5971 | 53.8556 | 30.6665 | 50.112 | 50.1177 | |
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| 1.8112 | 6.0 | 33066 | 1.5649 | 54.179 | 31.0178 | 50.407 | 50.4281 | |
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| 1.7644 | 7.0 | 38577 | 1.5605 | 54.3104 | 30.7997 | 50.4555 | 50.4861 | |
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| 1.7265 | 8.0 | 44088 | 1.5447 | 54.5593 | 31.0283 | 50.6343 | 50.6605 | |
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| 1.7013 | 9.0 | 49599 | 1.5440 | 54.7385 | 31.3073 | 50.9111 | 50.9334 | |
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| 1.6864 | 10.0 | 55110 | 1.5399 | 54.613 | 31.1543 | 50.7709 | 50.7907 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.1.0 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
