---
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-emails-gpt-summaries-batchs8-epochs20
  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-emails-gpt-summaries-batchs8-epochs20

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: 3.0969
- Rouge1: 0.1523
- Rouge2: 0.0732
- Rougel: 0.1381
- Rougelsum: 0.1512

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 20.8315       | 1.0   | 18   | 12.1572         | 0.0110 | 0.0    | 0.0110 | 0.0110    |
| 16.2522       | 2.0   | 36   | 9.4668          | 0.0172 | 0.0025 | 0.0172 | 0.0168    |
| 13.8556       | 3.0   | 54   | 8.5239          | 0.0149 | 0.0025 | 0.0152 | 0.0146    |
| 11.5721       | 4.0   | 72   | 7.3135          | 0.0128 | 0.0013 | 0.0128 | 0.0125    |
| 10.2536       | 5.0   | 90   | 7.3664          | 0.0118 | 0.0013 | 0.0120 | 0.0115    |
| 8.8152        | 6.0   | 108  | 5.2895          | 0.0288 | 0.0070 | 0.0290 | 0.0286    |
| 7.909         | 7.0   | 126  | 3.9341          | 0.0285 | 0.0013 | 0.0284 | 0.0281    |
| 6.7655        | 8.0   | 144  | 3.6549          | 0.0427 | 0.0069 | 0.0406 | 0.0394    |
| 6.243         | 9.0   | 162  | 3.5561          | 0.0474 | 0.0133 | 0.0437 | 0.0462    |
| 5.5584        | 10.0  | 180  | 3.4047          | 0.0823 | 0.0253 | 0.0786 | 0.0763    |
| 5.1966        | 11.0  | 198  | 3.3160          | 0.1221 | 0.0484 | 0.1186 | 0.1209    |
| 4.9761        | 12.0  | 216  | 3.2536          | 0.1469 | 0.0751 | 0.1364 | 0.1481    |
| 4.7006        | 13.0  | 234  | 3.2081          | 0.1353 | 0.0637 | 0.1162 | 0.1318    |
| 4.4686        | 14.0  | 252  | 3.1687          | 0.1453 | 0.0707 | 0.1347 | 0.1399    |
| 4.3912        | 15.0  | 270  | 3.1480          | 0.1574 | 0.0782 | 0.1449 | 0.1498    |
| 4.2511        | 16.0  | 288  | 3.1414          | 0.1541 | 0.0734 | 0.1412 | 0.1509    |
| 4.1233        | 17.0  | 306  | 3.1239          | 0.1572 | 0.0734 | 0.1439 | 0.1536    |
| 4.0948        | 18.0  | 324  | 3.1061          | 0.1451 | 0.0689 | 0.1316 | 0.1438    |
| 4.0434        | 19.0  | 342  | 3.0981          | 0.1517 | 0.0732 | 0.1377 | 0.1507    |
| 4.1557        | 20.0  | 360  | 3.0969          | 0.1523 | 0.0732 | 0.1381 | 0.1512    |


### Framework versions

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