transformers tensorboard safetensors mt5 text2text-generation summarization generated_from_trainer base_model:google/mt5-small base_model:finetune:google/mt5-small license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
base_model: google/mt5-small
library_name: transformers
license: apache-2.0
metrics:
- rouge
tags:
- summarization
- generated_from_trainer
model-index:
- name: mt5-small-finetuned-xlsum-zh-en
  results: []
---

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# mt5-small-finetuned-xlsum-zh-en

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4765
- Rouge1: 13.6815
- Rouge2: 1.9963
- Rougel: 11.1618
- Rougelsum: 11.196

## 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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 4.179         | 1.0   | 175  | 3.4764          | 12.6283 | 1.9745 | 10.3319 | 10.3779   |
| 3.9528        | 2.0   | 350  | 3.4743          | 13.3663 | 1.992  | 11.0757 | 11.0275   |
| 3.8472        | 3.0   | 525  | 3.4887          | 12.8037 | 1.8678 | 10.3381 | 10.3357   |
| 3.7711        | 4.0   | 700  | 3.4765          | 13.6815 | 1.9963 | 11.1618 | 11.196    |
| 3.7389        | 5.0   | 875  | 3.4853          | 13.1565 | 1.9543 | 10.6958 | 10.7191   |
| 3.7368        | 6.0   | 1050 | 3.4717          | 13.025  | 1.9673 | 10.5016 | 10.5047   |
| 3.7475        | 7.0   | 1225 | 3.4678          | 12.7763 | 1.8506 | 10.3091 | 10.3242   |
| 3.783         | 8.0   | 1400 | 3.4659          | 12.9145 | 1.9185 | 10.3757 | 10.4012   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.2.2+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
