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---
library_name: transformers
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-amazon-en-es
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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2696
- Rouge1: 18.0077
- Rouge2: 8.9356
- Rougel: 17.0726
- Rougelsum: 17.49
## 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 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 2.9554 | 1.0 | 771 | 3.4803 | 15.042 | 7.3797 | 14.3849 | 14.6833 |
| 3.4215 | 2.0 | 1542 | 3.3163 | 18.4061 | 9.6431 | 17.5021 | 17.7826 |
| 3.291 | 3.0 | 2313 | 3.2730 | 17.2129 | 9.3229 | 16.4817 | 16.7271 |
| 3.2173 | 4.0 | 3084 | 3.2753 | 18.8265 | 9.6163 | 17.8975 | 18.2779 |
| 3.1352 | 5.0 | 3855 | 3.2602 | 18.1662 | 8.848 | 17.3152 | 17.6519 |
| 3.0988 | 6.0 | 4626 | 3.2715 | 17.8952 | 9.1387 | 16.9838 | 17.4692 |
| 3.0745 | 7.0 | 5397 | 3.2663 | 17.5901 | 8.517 | 16.636 | 17.0347 |
| 3.0408 | 8.0 | 6168 | 3.2696 | 18.0077 | 8.9356 | 17.0726 | 17.49 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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