---
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-summarize
  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-summarize

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1534
- Rouge1: 0.3153
- Rouge2: 0.1594
- Rougel: 0.2511
- Rougelsum: 0.3397

## 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: 0.0005
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 90
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 4.3806        | 1.0667 | 100  | 3.4709          | 0.2568 | 0.1258 | 0.2214 | 0.2662    |
| 3.7757        | 2.1333 | 200  | 3.2899          | 0.2759 | 0.1388 | 0.2381 | 0.2946    |
| 3.5195        | 3.2    | 300  | 3.1951          | 0.2951 | 0.1523 | 0.2466 | 0.3217    |
| 3.4319        | 4.2667 | 400  | 3.1715          | 0.2813 | 0.1323 | 0.2331 | 0.3011    |
| 3.2402        | 5.3333 | 500  | 3.1704          | 0.3058 | 0.1548 | 0.2513 | 0.3366    |
| 3.2313        | 6.4    | 600  | 3.1657          | 0.3077 | 0.1534 | 0.2461 | 0.3335    |
| 3.1444        | 7.4667 | 700  | 3.1719          | 0.2957 | 0.1453 | 0.2378 | 0.3191    |
| 3.116         | 8.5333 | 800  | 3.1639          | 0.3144 | 0.1540 | 0.2501 | 0.3453    |
| 2.9937        | 9.6    | 900  | 3.1534          | 0.3153 | 0.1594 | 0.2511 | 0.3397    |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1