metadata
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
datasets:
- scientific_papers
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-amazon-en-es
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: scientific_papers
type: scientific_papers
config: pubmed
split: validation
args: pubmed
metrics:
- name: Rouge1
type: rouge
value: 7.0145
mt5-small-finetuned-amazon-en-es
This model is a fine-tuned version of google/mt5-small on the scientific_papers dataset. It achieves the following results on the evaluation set:
- Loss: 3.5188
- Rouge1: 7.0145
- Rouge2: 1.8214
- Rougel: 5.8355
- Rougelsum: 6.2468
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 17.5935 | 1.0 | 50 | 8.3763 | 1.0909 | 0.7547 | 1.0909 | 1.0909 |
| 10.9464 | 2.0 | 100 | 4.7599 | 3.5415 | 0.0 | 2.927 | 2.547 |
| 6.5498 | 3.0 | 150 | 3.6772 | 6.7136 | 1.8214 | 5.2193 | 5.925 |
| 6.0161 | 4.0 | 200 | 3.5188 | 7.0145 | 1.8214 | 5.8355 | 6.2468 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.1+cpu
- Datasets 2.17.0
- Tokenizers 0.15.2