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---
library_name: transformers
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-amazon-en-fr
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-small-finetuned-amazon-en-es
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: 3.0056
- Rouge1: 16.1556
- Rouge2: 8.8085
- Rougel: 15.8019
- Rougelsum: 15.7787
## 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 adamw_torch_fused 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 6.9474 | 1.0 | 1399 | 3.3187 | 11.4251 | 4.57 | 10.9308 | 10.7649 |
| 3.892 | 2.0 | 2798 | 3.1469 | 13.4445 | 6.2409 | 13.013 | 12.9006 |
| 3.5863 | 3.0 | 4197 | 3.0734 | 15.1812 | 8.3203 | 14.7922 | 14.7632 |
| 3.4229 | 4.0 | 5596 | 3.0587 | 16.1014 | 8.4524 | 15.8047 | 15.7134 |
| 3.326 | 5.0 | 6995 | 3.0234 | 17.153 | 9.3495 | 16.6487 | 16.564 |
| 3.2622 | 6.0 | 8394 | 3.0144 | 15.5588 | 8.1691 | 15.275 | 15.2065 |
| 3.2163 | 7.0 | 9793 | 3.0139 | 15.8487 | 8.6641 | 15.548 | 15.511 |
| 3.1948 | 8.0 | 11192 | 3.0056 | 16.1556 | 8.8085 | 15.8019 | 15.7787 |
### Framework versions
- Transformers 4.55.4
- Pytorch 2.8.0+cu128
- Datasets 4.0.0
- Tokenizers 0.21.4
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