metadata
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-amazon-en-es
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: xsum
type: xsum
config: default
split: validation
args: default
metrics:
- name: Rouge1
type: rouge
value: 0.0524
mt5-small-finetuned-amazon-en-es
This model is a fine-tuned version of google/mt5-small on the xsum dataset. It achieves the following results on the evaluation set:
- Loss: 8.0085
- Rouge1: 0.0524
- Rouge2: 0.0083
- Rougel: 0.0416
- Rougelsum: 0.0416
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: 32
- eval_batch_size: 32
- 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 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 4 | 12.7017 | 0.0208 | 0.0 | 0.0148 | 0.0148 |
| No log | 2.0 | 8 | 10.3879 | 0.0208 | 0.0 | 0.0148 | 0.0148 |
| 18.6837 | 3.0 | 12 | 9.1367 | 0.0208 | 0.0 | 0.0148 | 0.0148 |
| 18.6837 | 4.0 | 16 | 8.6067 | 0.0269 | 0.0 | 0.0209 | 0.0209 |
| 18.6837 | 5.0 | 20 | 8.2033 | 0.0377 | 0.0 | 0.026 | 0.0256 |
| 15.292 | 6.0 | 24 | 8.1000 | 0.0524 | 0.0083 | 0.0416 | 0.0416 |
| 15.292 | 7.0 | 28 | 8.0750 | 0.0524 | 0.0083 | 0.0416 | 0.0416 |
| 15.292 | 8.0 | 32 | 8.0085 | 0.0524 | 0.0083 | 0.0416 | 0.0416 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu118
- Datasets 2.17.1
- Tokenizers 0.15.2