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---
license: apache-2.0
base_model: LinhCT/mt5-small-finetuned-amazon-en-es
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-amazon-en-es-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-finetuned-amazon-en-es
This model is a fine-tuned version of [LinhCT/mt5-small-finetuned-amazon-en-es](https://huggingface.co/LinhCT/mt5-small-finetuned-amazon-en-es) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4243
- Rouge1: 28.2282
- Rouge2: 13.0079
- Rougel: 27.8476
- Rougelsum: 27.9373
## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 5.1931 | 1.0 | 1152 | 3.7893 | 19.9416 | 8.7882 | 19.7175 | 19.6944 |
| 4.2391 | 2.0 | 2304 | 3.6033 | 24.7762 | 11.4627 | 24.5132 | 24.5349 |
| 3.9401 | 3.0 | 3456 | 3.5088 | 25.618 | 11.8757 | 25.316 | 25.3784 |
| 3.7617 | 4.0 | 4608 | 3.4602 | 26.2721 | 11.8065 | 25.9693 | 26.0518 |
| 3.6381 | 5.0 | 5760 | 3.4439 | 27.3459 | 12.668 | 26.9862 | 27.0528 |
| 3.548 | 6.0 | 6912 | 3.4317 | 27.751 | 12.7711 | 27.3445 | 27.3912 |
| 3.4956 | 7.0 | 8064 | 3.4343 | 28.7685 | 13.1835 | 28.3702 | 28.4383 |
| 3.4589 | 8.0 | 9216 | 3.4243 | 28.2282 | 13.0079 | 27.8476 | 27.9373 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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