---
license: apache-2.0
base_model: google/mt5-base
tags:
- generated_from_trainer
metrics:
- rouge
- sacrebleu
model-index:
- name: mT5-TextSimp-LT-BatchSize8-lr5e-5
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# mT5-TextSimp-LT-BatchSize8-lr5e-5

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: 0.0983
- Rouge1: 0.6245
- Rouge2: 0.4439
- Rougel: 0.6142
- Sacrebleu: 35.7192
- 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: 5e-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
- lr_scheduler_warmup_steps: 500
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Sacrebleu | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------:|
| 35.3898       | 0.96  | 200  | 27.6372         | 0.0019 | 0.0    | 0.0018 | 0.0003    | 512.0    |
| 3.5712        | 1.91  | 400  | 1.9615          | 0.0171 | 0.0    | 0.0167 | 0.0225    | 39.0501  |
| 0.6489        | 2.87  | 600  | 0.5638          | 0.0052 | 0.0    | 0.0051 | 0.0256    | 39.0501  |
| 0.6017        | 3.83  | 800  | 3.2823          | 0.2419 | 0.1287 | 0.2318 | 0.6457    | 130.3556 |
| 0.3784        | 4.78  | 1000 | 0.1340          | 0.5092 | 0.3277 | 0.4978 | 26.7005   | 38.0549  |
| 0.1521        | 5.74  | 1200 | 0.1092          | 0.5782 | 0.3973 | 0.5672 | 33.2443   | 38.0501  |
| 0.2096        | 6.7   | 1400 | 0.1001          | 0.6149 | 0.4342 | 0.6046 | 34.6518   | 38.0501  |
| 0.1719        | 7.66  | 1600 | 0.0983          | 0.6245 | 0.4439 | 0.6142 | 35.7192   | 38.0501  |


### Framework versions

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