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---
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- T2SAM
- abstractive summarization
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-inshorts-news-summary
results: []
language:
- en
library_name: transformers
datasets:
- sandeep16064/news_summary
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mt5-small-finetuned-inshorts-news-summary
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).
It achieves the following results on the evaluation set:
- Loss: 1.5399
- Rouge1: 54.613
- Rouge2: 31.1543
- Rougel: 50.7709
- Rougelsum: 50.7907
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 3.3244 | 1.0 | 5511 | 1.8904 | 51.0778 | 28.3112 | 47.4136 | 47.404 |
| 2.2747 | 2.0 | 11022 | 1.7450 | 51.8372 | 28.9814 | 48.0917 | 48.0965 |
| 2.0745 | 3.0 | 16533 | 1.6567 | 52.518 | 29.7276 | 48.727 | 48.7504 |
| 1.9516 | 4.0 | 22044 | 1.6210 | 54.2404 | 30.8927 | 50.4042 | 50.3996 |
| 1.8714 | 5.0 | 27555 | 1.5971 | 53.8556 | 30.6665 | 50.112 | 50.1177 |
| 1.8112 | 6.0 | 33066 | 1.5649 | 54.179 | 31.0178 | 50.407 | 50.4281 |
| 1.7644 | 7.0 | 38577 | 1.5605 | 54.3104 | 30.7997 | 50.4555 | 50.4861 |
| 1.7265 | 8.0 | 44088 | 1.5447 | 54.5593 | 31.0283 | 50.6343 | 50.6605 |
| 1.7013 | 9.0 | 49599 | 1.5440 | 54.7385 | 31.3073 | 50.9111 | 50.9334 |
| 1.6864 | 10.0 | 55110 | 1.5399 | 54.613 | 31.1543 | 50.7709 | 50.7907 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0
- Datasets 2.12.0
- Tokenizers 0.13.3 |