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---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-amazon-en-es
results:
- task:
type: summarization
name: Summarization
dataset:
name: cnn_dailymail
type: cnn_dailymail
config: 3.0.0
split: test
metrics:
- type: rouge
value: 5.5685
name: ROUGE-1
verified: true
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- type: rouge
value: 1.5241
name: ROUGE-2
verified: true
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- type: rouge
value: 4.6568
name: ROUGE-L
verified: true
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- type: rouge
value: 5.2235
name: ROUGE-LSUM
verified: true
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- type: loss
value: 3.6021058559417725
name: loss
verified: true
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- type: gen_len
value: 9.3862
name: gen_len
verified: true
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---
<!-- 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: 3.0294
- Rouge1: 16.6807
- Rouge2: 8.0004
- Rougel: 16.2251
- Rougelsum: 16.1743
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 6.5928 | 1.0 | 1209 | 3.3005 | 14.7863 | 6.5038 | 14.3031 | 14.2522 |
| 3.9024 | 2.0 | 2418 | 3.1399 | 16.9257 | 8.6583 | 16.15 | 16.1299 |
| 3.5806 | 3.0 | 3627 | 3.0869 | 18.2734 | 9.1667 | 17.7441 | 17.5782 |
| 3.4201 | 4.0 | 4836 | 3.0590 | 17.763 | 8.9447 | 17.1833 | 17.1661 |
| 3.3202 | 5.0 | 6045 | 3.0598 | 17.7754 | 8.5695 | 17.4139 | 17.2653 |
| 3.2436 | 6.0 | 7254 | 3.0409 | 16.8423 | 8.1593 | 16.5392 | 16.4297 |
| 3.2079 | 7.0 | 8463 | 3.0332 | 16.8991 | 8.1574 | 16.4229 | 16.3515 |
| 3.1801 | 8.0 | 9672 | 3.0294 | 16.6807 | 8.0004 | 16.2251 | 16.1743 |
### Framework versions
- Transformers 4.22.1
- Pytorch 1.12.1+cu113
- Datasets 2.5.1
- Tokenizers 0.12.1
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