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---
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
datasets:
- web_nlg
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-amazon-en-es
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: web_nlg
type: web_nlg
config: en
split: validation
args: en
metrics:
- name: Rouge1
type: rouge
value: 76.7573
---
<!-- 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 web_nlg dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1274
- Rouge1: 76.7573
- Rouge2: 70.2881
- Rougel: 74.6384
- Rougelsum: 74.6743
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 1.9276 | 1.0 | 4429 | 0.4272 | 68.6843 | 56.7537 | 65.8818 | 65.9389 |
| 0.5548 | 2.0 | 8858 | 0.2903 | 72.0968 | 62.884 | 69.6164 | 69.6271 |
| 0.3936 | 3.0 | 13287 | 0.2308 | 73.8306 | 65.8224 | 71.4996 | 71.4971 |
| 0.3093 | 4.0 | 17716 | 0.1632 | 75.0861 | 67.7273 | 72.9128 | 72.9615 |
| 0.2592 | 5.0 | 22145 | 0.1484 | 75.7699 | 68.7078 | 73.5831 | 73.5905 |
| 0.2295 | 6.0 | 26574 | 0.1353 | 76.4394 | 69.689 | 74.3168 | 74.3496 |
| 0.2117 | 7.0 | 31003 | 0.1289 | 76.6532 | 69.9438 | 74.5065 | 74.5616 |
| 0.2026 | 8.0 | 35432 | 0.1274 | 76.7573 | 70.2881 | 74.6384 | 74.6743 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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