|
--- |
|
license: apache-2.0 |
|
tags: |
|
- summarization |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: mt5-small-finetuned-amazon-en-es-Resumen-2 |
|
results: [] |
|
--- |
|
|
|
<!-- 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-Resumen-2 |
|
|
|
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 3.0910 |
|
- Rouge1: 16.3799 |
|
- Rouge2: 7.6088 |
|
- Rougel: 15.9886 |
|
- Rougelsum: 16.1691 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:| |
|
| 7.004 | 1.0 | 1209 | 3.3408 | 13.3874 | 5.2828 | 12.9812 | 12.9666 | |
|
| 3.9036 | 2.0 | 2418 | 3.2286 | 15.9158 | 7.7591 | 15.2863 | 15.3932 | |
|
| 3.598 | 3.0 | 3627 | 3.1778 | 16.0628 | 7.1178 | 15.1227 | 15.2487 | |
|
| 3.4228 | 4.0 | 4836 | 3.1147 | 15.9998 | 7.6239 | 15.3691 | 15.4711 | |
|
| 3.3212 | 5.0 | 6045 | 3.1049 | 16.5369 | 7.743 | 16.2272 | 16.3427 | |
|
| 3.2658 | 6.0 | 7254 | 3.0974 | 17.4125 | 8.0961 | 17.0223 | 17.136 | |
|
| 3.2105 | 7.0 | 8463 | 3.0911 | 16.5786 | 7.7369 | 16.1889 | 16.3189 | |
|
| 3.184 | 8.0 | 9672 | 3.0910 | 16.3799 | 7.6088 | 15.9886 | 16.1691 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.21.0 |
|
- Pytorch 1.12.0+cu113 |
|
- Datasets 2.4.0 |
|
- Tokenizers 0.12.1 |
|
|
