---
license: apache-2.0
base_model: google/mt5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mT5-TextSimp-LT-BatchSize12-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-BatchSize12-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: 0.1611
- Rouge1: 0.4599
- Rouge2: 0.2777
- Rougel: 0.4471
- Gen Len: 39.0358

## 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: 4
- eval_batch_size: 4
- 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 | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:--------:|
| 36.6446       | 0.48  | 200  | 31.2765         | 0.0004 | 0.0    | 0.0004 | 512.0    |
| 11.5223       | 0.96  | 400  | 6.7786          | 0.003  | 0.0    | 0.0031 | 89.2816  |
| 2.2686        | 1.44  | 600  | 0.6729          | 0.0053 | 0.0    | 0.0053 | 39.0501  |
| 0.7009        | 1.91  | 800  | 0.6529          | 0.0029 | 0.0    | 0.0027 | 41.401   |
| 0.6213        | 2.39  | 1000 | 0.5630          | 0.0057 | 0.0002 | 0.0056 | 39.0334  |
| 0.6435        | 2.87  | 1200 | 0.4697          | 0.0685 | 0.0084 | 0.0611 | 39.0453  |
| 0.4154        | 3.35  | 1400 | 10.4655         | 0.2093 | 0.1217 | 0.2006 | 350.0334 |
| 0.6289        | 3.83  | 1600 | 1.9257          | 0.317  | 0.1946 | 0.3064 | 138.7494 |
| 3.5542        | 4.31  | 1800 | 0.8459          | 0.3735 | 0.204  | 0.3613 | 59.8568  |
| 8.1736        | 4.78  | 2000 | 7.2350          | 0.3144 | 0.1819 | 0.3037 | 289.1432 |
| 2.3987        | 5.26  | 2200 | 0.8361          | 0.3621 | 0.1911 | 0.351  | 61.0668  |
| 0.9853        | 5.74  | 2400 | 0.4219          | 0.3634 | 0.2008 | 0.352  | 46.494   |
| 0.3575        | 6.22  | 2600 | 0.3516          | 0.3805 | 0.2128 | 0.3689 | 46.1623  |
| 0.4497        | 6.7   | 2800 | 0.2597          | 0.4388 | 0.2698 | 0.4269 | 42.2697  |
| 0.2582        | 7.18  | 3000 | 0.1583          | 0.4444 | 0.2587 | 0.4316 | 38.1671  |
| 0.2629        | 7.66  | 3200 | 0.1611          | 0.4599 | 0.2777 | 0.4471 | 39.0358  |


### Framework versions

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