---
license: apache-2.0
base_model: google/mt5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-base-finetuned-test_30483_prefix_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-base-finetuned-test_30483_prefix_summarize

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: 2.3527
- Rouge1: 23.6141
- Rouge2: 7.1791
- Rougel: 16.0152
- Rougelsum: 21.8213
- Gen Len: 69.64

## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 7.4668        | 1.25  | 500  | 2.6478          | 10.4597 | 4.2457 | 8.7184  | 9.8473    | 18.49   |
| 3.3231        | 2.5   | 1000 | 2.5146          | 17.7315 | 6.0795 | 13.5384 | 16.6839   | 40.55   |
| 3.0956        | 3.75  | 1500 | 2.4512          | 20.2871 | 6.4051 | 14.8508 | 18.8768   | 51.35   |
| 2.9928        | 5.0   | 2000 | 2.4180          | 21.4196 | 6.629  | 15.2607 | 20.1471   | 57.92   |
| 2.8802        | 6.25  | 2500 | 2.4030          | 21.7949 | 6.7926 | 15.2506 | 20.338    | 61.05   |
| 2.8243        | 7.5   | 3000 | 2.3856          | 21.7075 | 6.7397 | 15.0044 | 20.1744   | 61.19   |
| 2.7646        | 8.75  | 3500 | 2.3847          | 22.4137 | 6.7644 | 14.9987 | 20.7797   | 63.81   |
| 2.7096        | 10.0  | 4000 | 2.3691          | 22.3403 | 6.9812 | 15.5411 | 20.6166   | 62.79   |
| 2.6758        | 11.25 | 4500 | 2.3612          | 23.6542 | 7.2355 | 15.9979 | 21.9807   | 69.83   |
| 2.6579        | 12.5  | 5000 | 2.3556          | 23.7473 | 7.5446 | 16.0314 | 21.917    | 69.75   |
| 2.651         | 13.75 | 5500 | 2.3557          | 23.9711 | 7.5018 | 16.2033 | 22.2811   | 69.29   |
| 2.639         | 15.0  | 6000 | 2.3527          | 23.6141 | 7.1791 | 16.0152 | 21.8213   | 69.64   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0
- Datasets 2.12.0
- Tokenizers 0.13.3