|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: google/mt5-small |
|
tags: |
|
- summarization |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: mt5-small-finetuned-amazon-en-es |
|
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 |
|
|
|
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 3.0303 |
|
- Rouge1: 16.5951 |
|
- Rouge2: 7.6416 |
|
- Rougel: 16.0871 |
|
- Rougelsum: 16.0029 |
|
|
|
## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
- lr_scheduler_type: linear |
|
- num_epochs: 8 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:| |
|
| 6.9675 | 1.0 | 1209 | 3.2986 | 15.3916 | 6.8734 | 14.8161 | 14.7319 | |
|
| 3.8997 | 2.0 | 2418 | 3.1665 | 16.2801 | 7.7394 | 15.7055 | 15.7013 | |
|
| 3.5826 | 3.0 | 3627 | 3.1106 | 17.0462 | 8.4851 | 16.5069 | 16.4118 | |
|
| 3.421 | 4.0 | 4836 | 3.0963 | 17.235 | 8.8167 | 16.7472 | 16.7047 | |
|
| 3.3089 | 5.0 | 6045 | 3.0490 | 16.6744 | 7.6767 | 16.1951 | 16.098 | |
|
| 3.2437 | 6.0 | 7254 | 3.0401 | 16.6011 | 7.9461 | 16.0163 | 15.9111 | |
|
| 3.2133 | 7.0 | 8463 | 3.0292 | 16.2951 | 7.6564 | 15.9059 | 15.857 | |
|
| 3.1851 | 8.0 | 9672 | 3.0303 | 16.5951 | 7.6416 | 16.0871 | 16.0029 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.46.2 |
|
- Pytorch 2.5.1+cu121 |
|
- Datasets 3.1.0 |
|
- Tokenizers 0.20.3 |
|
|
