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---
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-xlsum-pt
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-xlsum-pt
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: 0.0986
- Rouge1: 16.5756
- Rouge2: 13.7639
- Rougel: 15.7445
- Rougelsum: 16.5112
## 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 0.7681 | 1.0 | 125 | 0.1393 | 12.9432 | 9.5039 | 12.2871 | 12.7291 |
| 0.5282 | 2.0 | 250 | 0.1231 | 13.4575 | 10.0697 | 12.6449 | 13.2 |
| 0.4132 | 3.0 | 375 | 0.1134 | 16.6964 | 14.0187 | 15.7338 | 16.6025 |
| 0.3534 | 4.0 | 500 | 0.1077 | 16.8961 | 14.2203 | 15.9187 | 16.7712 |
| 0.3126 | 5.0 | 625 | 0.1039 | 16.993 | 14.0876 | 15.8914 | 16.9277 |
| 0.283 | 6.0 | 750 | 0.1023 | 16.7431 | 13.9453 | 15.8758 | 16.6413 |
| 0.2675 | 7.0 | 875 | 0.1008 | 16.6566 | 13.8639 | 15.775 | 16.5481 |
| 0.2509 | 8.0 | 1000 | 0.0987 | 16.6829 | 13.935 | 15.872 | 16.6222 |
| 0.2441 | 9.0 | 1125 | 0.0987 | 16.6085 | 13.7884 | 15.7896 | 16.5412 |
| 0.2401 | 10.0 | 1250 | 0.0986 | 16.5756 | 13.7639 | 15.7445 | 16.5112 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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