transformers pytorch tensorboard mt5 text2text-generation summarization generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
metrics:
- rouge
tags:
- summarization
- generated_from_trainer
model-index:
- name: mt5-small-finetuned-amazon-en-zh
  results: []
---

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# mt5-small-finetuned-amazon-en-zh

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: 3.3029
- Rouge1: 16.5328
- Rouge2: 7.1687
- Rougel: 15.8574
- Rougelsum: 16.1506

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 6.5452        | 1.0   | 1676  | 3.5344          | 13.2336 | 4.9489 | 12.9231 | 13.033    |
| 3.803         | 2.0   | 3352  | 3.3963          | 14.814  | 6.2391 | 14.2581 | 14.4316   |
| 3.4981        | 3.0   | 5028  | 3.3262          | 16.6892 | 7.7862 | 15.9537 | 16.1894   |
| 3.3061        | 4.0   | 6704  | 3.3111          | 15.4591 | 7.1128 | 14.6644 | 14.7762   |
| 3.2023        | 5.0   | 8380  | 3.3039          | 15.7126 | 7.1817 | 14.895  | 15.1448   |
| 3.1173        | 6.0   | 10056 | 3.3094          | 16.1592 | 7.609  | 15.4639 | 15.5988   |
| 3.0803        | 7.0   | 11732 | 3.2999          | 16.2882 | 7.1004 | 15.7029 | 15.8878   |
| 3.0539        | 8.0   | 13408 | 3.3029          | 16.5328 | 7.1687 | 15.8574 | 16.1506   |


### Framework versions

- Transformers 4.27.4
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2
