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---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- mlsum
metrics:
- rouge
base_model: google/mt5-small
model-index:
- name: mt5-small-test-ged-mlsum_max_target_length_10
results:
- task:
type: text2text-generation
name: Sequence-to-sequence Language Modeling
dataset:
name: mlsum
type: mlsum
args: es
metrics:
- type: rouge
value: 74.8229
name: Rouge1
---
<!-- 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-test-ged-mlsum_max_target_length_10
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the mlsum dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3341
- Rouge1: 74.8229
- Rouge2: 68.1808
- Rougel: 74.8297
- Rougelsum: 74.8414
## 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 |
|:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 0.5565 | 1.0 | 33296 | 0.3827 | 69.9041 | 62.821 | 69.8709 | 69.8924 |
| 0.2636 | 2.0 | 66592 | 0.3552 | 72.0701 | 65.4937 | 72.0787 | 72.091 |
| 0.2309 | 3.0 | 99888 | 0.3525 | 72.5071 | 65.8026 | 72.5132 | 72.512 |
| 0.2109 | 4.0 | 133184 | 0.3346 | 74.0842 | 67.4776 | 74.0887 | 74.0968 |
| 0.1972 | 5.0 | 166480 | 0.3398 | 74.6051 | 68.6024 | 74.6177 | 74.6365 |
| 0.1867 | 6.0 | 199776 | 0.3283 | 74.9022 | 68.2146 | 74.9023 | 74.926 |
| 0.1785 | 7.0 | 233072 | 0.3325 | 74.8631 | 68.2468 | 74.8843 | 74.9026 |
| 0.1725 | 8.0 | 266368 | 0.3341 | 74.8229 | 68.1808 | 74.8297 | 74.8414 |
### Framework versions
- Transformers 4.20.0
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
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