---
license: apache-2.0
base_model: google/mt5-base
tags:
- generated_from_trainer
metrics:
- rouge
- sacrebleu
model-index:
- name: mT5-TextSimp-LT-BatchSize8-lr1e-4
  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-TextSimp-LT-BatchSize8-lr1e-4

This model is a fine-tuned version of [google/mt5-base](https://huggingface.co./google/mt5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0826
- Rouge1: 0.6956
- Rouge2: 0.532
- Rougel: 0.6875
- Sacrebleu: 41.0349
- Gen Len: 38.0501

## 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: 0.0001
- 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Sacrebleu | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 22.5133       | 0.96  | 200  | 14.4822         | 0.0057 | 0.0    | 0.0056 | 0.0013    | 512.0   |
| 1.0276        | 1.91  | 400  | 0.7352          | 0.022  | 0.0005 | 0.0215 | 0.0232    | 41.4702 |
| 0.6477        | 2.87  | 600  | 1.5193          | 0.1021 | 0.012  | 0.0954 | 0.0573    | 83.3723 |
| 0.1784        | 3.83  | 800  | 0.1149          | 0.6014 | 0.4222 | 0.5898 | 32.2723   | 38.0501 |
| 0.158         | 4.78  | 1000 | 0.0930          | 0.6546 | 0.4822 | 0.6463 | 37.3842   | 38.0501 |
| 0.1059        | 5.74  | 1200 | 0.0884          | 0.6714 | 0.4983 | 0.6635 | 39.0129   | 38.0501 |
| 0.1542        | 6.7   | 1400 | 0.0830          | 0.688  | 0.5184 | 0.6803 | 40.419    | 38.0501 |
| 0.1206        | 7.66  | 1600 | 0.0826          | 0.6956 | 0.532  | 0.6875 | 41.0349   | 38.0501 |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.1.2+cu121
- Datasets 2.14.4
- Tokenizers 0.13.3