|
--- |
|
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 the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 3.0349 |
|
- Rouge1: 17.111 |
|
- Rouge2: 8.39 |
|
- Rougel: 16.7227 |
|
- Rougelsum: 16.7209 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:| |
|
| 7.3401 | 1.0 | 1209 | 3.3465 | 14.0925 | 6.2495 | 13.7784 | 13.9647 | |
|
| 3.9195 | 2.0 | 2418 | 3.1859 | 16.0052 | 8.1545 | 15.4495 | 15.5175 | |
|
| 3.5975 | 3.0 | 3627 | 3.0945 | 17.4726 | 9.0998 | 16.9741 | 17.1364 | |
|
| 3.4241 | 4.0 | 4836 | 3.0913 | 16.3822 | 7.7661 | 15.852 | 15.9198 | |
|
| 3.3252 | 5.0 | 6045 | 3.0588 | 16.6252 | 8.1458 | 16.1867 | 16.2189 | |
|
| 3.2442 | 6.0 | 7254 | 3.0444 | 17.1532 | 8.4258 | 16.7123 | 16.7598 | |
|
| 3.2149 | 7.0 | 8463 | 3.0355 | 17.4131 | 8.7262 | 17.0104 | 17.0702 | |
|
| 3.184 | 8.0 | 9672 | 3.0349 | 17.111 | 8.39 | 16.7227 | 16.7209 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.33.2 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.13.3 |
|
|
