|
--- |
|
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: 0.0899 |
|
--- |
|
|
|
<!-- 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 xsum dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 3.6525 |
|
- Rouge1: 0.0899 |
|
- Rouge2: 0.0226 |
|
- Rougel: 0.0821 |
|
- Rougelsum: 0.0807 |
|
|
|
## 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: 8 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| |
|
| 18.5949 | 1.0 | 50 | 8.8110 | 0.0298 | 0.0 | 0.0298 | 0.0298 | |
|
| 10.7742 | 2.0 | 100 | 5.1285 | 0.087 | 0.0087 | 0.0805 | 0.0796 | |
|
| 7.6938 | 3.0 | 150 | 4.3645 | 0.0684 | 0.0 | 0.0579 | 0.0615 | |
|
| 6.3393 | 4.0 | 200 | 4.0164 | 0.035 | 0.0 | 0.0355 | 0.035 | |
|
| 5.9075 | 5.0 | 250 | 3.7881 | 0.0579 | 0.0065 | 0.051 | 0.0528 | |
|
| 5.7394 | 6.0 | 300 | 3.6971 | 0.0749 | 0.0226 | 0.0733 | 0.0733 | |
|
| 5.4246 | 7.0 | 350 | 3.6652 | 0.0749 | 0.0226 | 0.0733 | 0.0733 | |
|
| 5.2963 | 8.0 | 400 | 3.6525 | 0.0899 | 0.0226 | 0.0821 | 0.0807 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.2 |
|
- Pytorch 2.2.1+cu118 |
|
- Datasets 2.17.1 |
|
- Tokenizers 0.15.2 |
|
|
