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---
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-amazon-en-es
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: xsum
type: xsum
config: default
split: validation
args: default
metrics:
- name: Rouge1
type: rouge
value: 0.0899
---
<!-- 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 xsum dataset.
It achieves the following results on the evaluation set:
- Loss: 3.6525
- Rouge1: 0.0899
- Rouge2: 0.0226
- Rougel: 0.0821
- Rougelsum: 0.0807
## 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: 2
- eval_batch_size: 2
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 18.5949 | 1.0 | 50 | 8.8110 | 0.0298 | 0.0 | 0.0298 | 0.0298 |
| 10.7742 | 2.0 | 100 | 5.1285 | 0.087 | 0.0087 | 0.0805 | 0.0796 |
| 7.6938 | 3.0 | 150 | 4.3645 | 0.0684 | 0.0 | 0.0579 | 0.0615 |
| 6.3393 | 4.0 | 200 | 4.0164 | 0.035 | 0.0 | 0.0355 | 0.035 |
| 5.9075 | 5.0 | 250 | 3.7881 | 0.0579 | 0.0065 | 0.051 | 0.0528 |
| 5.7394 | 6.0 | 300 | 3.6971 | 0.0749 | 0.0226 | 0.0733 | 0.0733 |
| 5.4246 | 7.0 | 350 | 3.6652 | 0.0749 | 0.0226 | 0.0733 | 0.0733 |
| 5.2963 | 8.0 | 400 | 3.6525 | 0.0899 | 0.0226 | 0.0821 | 0.0807 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu118
- Datasets 2.17.1
- Tokenizers 0.15.2
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