metadata
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
datasets:
- wcep-10
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-amazon-en-es
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: wcep-10
type: wcep-10
config: roberta
split: validation
args: roberta
metrics:
- name: Rouge1
type: rouge
value: 22.6862
mt5-small-finetuned-amazon-en-es
This model is a fine-tuned version of google/mt5-small on the wcep-10 dataset. It achieves the following results on the evaluation set:
- Loss: 3.1575
- Rouge1: 22.6862
- Rouge2: 7.7268
- Rougel: 19.1961
- Rougelsum: 19.3808
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 |
|---|---|---|---|---|---|---|---|
| 6.5905 | 1.0 | 1020 | 3.4711 | 21.2268 | 7.4345 | 18.5023 | 18.6264 |
| 4.1604 | 2.0 | 2040 | 3.3228 | 21.6354 | 7.3939 | 18.4926 | 18.6047 |
| 3.914 | 3.0 | 3060 | 3.2606 | 21.9787 | 7.5818 | 18.6971 | 18.8603 |
| 3.7698 | 4.0 | 4080 | 3.2058 | 21.8859 | 7.5625 | 18.6413 | 18.8169 |
| 3.679 | 5.0 | 5100 | 3.1824 | 22.6515 | 7.7467 | 19.1196 | 19.3121 |
| 3.6131 | 6.0 | 6120 | 3.1678 | 22.0223 | 7.6153 | 18.7956 | 18.9968 |
| 3.5722 | 7.0 | 7140 | 3.1631 | 22.679 | 7.7952 | 19.1784 | 19.384 |
| 3.5432 | 8.0 | 8160 | 3.1575 | 22.6862 | 7.7268 | 19.1961 | 19.3808 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1