---
library_name: transformers
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-Drishtants-summaries
  results: []
---

<!-- 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-Drishtants-summaries

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7354
- Rouge1: 0.0368
- Rouge2: 0.0186
- Rougel: 0.0344
- Rougelsum: 0.0335

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 21.5975       | 1.0   | 18   | 11.3745         | 0.0    | 0.0    | 0.0    | 0.0       |
| 18.236        | 2.0   | 36   | 10.6384         | 0.0102 | 0.0    | 0.0102 | 0.0102    |
| 15.5742       | 3.0   | 54   | 9.9438          | 0.0201 | 0.0084 | 0.0160 | 0.0160    |
| 13.9098       | 4.0   | 72   | 8.4129          | 0.0250 | 0.0084 | 0.0209 | 0.0245    |
| 12.3694       | 5.0   | 90   | 6.1433          | 0.0250 | 0.0084 | 0.0209 | 0.0245    |
| 10.7687       | 6.0   | 108  | 6.1726          | 0.0102 | 0.0    | 0.0102 | 0.0102    |
| 9.4084        | 7.0   | 126  | 5.0390          | 0.0102 | 0.0    | 0.0102 | 0.0102    |
| 8.532         | 8.0   | 144  | 4.2376          | 0.0135 | 0.0    | 0.0139 | 0.0127    |
| 7.7273        | 9.0   | 162  | 3.8524          | 0.0268 | 0.0    | 0.0259 | 0.0258    |
| 6.9872        | 10.0  | 180  | 3.6113          | 0.0512 | 0.0070 | 0.0462 | 0.0425    |
| 6.4007        | 11.0  | 198  | 3.3596          | 0.0489 | 0.0118 | 0.0500 | 0.0496    |
| 6.021         | 12.0  | 216  | 3.2024          | 0.0441 | 0.0173 | 0.0403 | 0.0392    |
| 5.6179        | 13.0  | 234  | 3.1161          | 0.0498 | 0.0173 | 0.0466 | 0.0454    |
| 5.2275        | 14.0  | 252  | 3.0076          | 0.0411 | 0.0217 | 0.0396 | 0.0382    |
| 4.9888        | 15.0  | 270  | 2.9215          | 0.0449 | 0.0217 | 0.0434 | 0.0433    |
| 4.7543        | 16.0  | 288  | 2.8484          | 0.0368 | 0.0186 | 0.0344 | 0.0335    |
| 4.5961        | 17.0  | 306  | 2.7913          | 0.0368 | 0.0186 | 0.0344 | 0.0335    |
| 4.4748        | 18.0  | 324  | 2.7587          | 0.0368 | 0.0186 | 0.0344 | 0.0335    |
| 4.4339        | 19.0  | 342  | 2.7405          | 0.0368 | 0.0186 | 0.0344 | 0.0335    |
| 4.4859        | 20.0  | 360  | 2.7354          | 0.0368 | 0.0186 | 0.0344 | 0.0335    |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0