|
--- |
|
license: apache-2.0 |
|
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: 2.5050 |
|
- Rouge1: 16.471 |
|
- Rouge2: 9.6857 |
|
- Rougel: 16.1028 |
|
- Rougelsum: 16.1929 |
|
- Gen Len: 7.4538 |
|
|
|
## 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: 8e-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 | Gen Len | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
|
| 5.9093 | 1.0 | 1209 | 2.8536 | 9.0682 | 7.3025 | 8.7377 | 8.88 | 3.5504 | |
|
| 3.2481 | 2.0 | 2418 | 2.6507 | 16.3535 | 11.0792 | 16.0699 | 16.135 | 7.1387 | |
|
| 2.9617 | 3.0 | 3627 | 2.5843 | 15.2778 | 9.4619 | 15.0177 | 15.0804 | 7.4118 | |
|
| 2.8128 | 4.0 | 4836 | 2.5501 | 15.9292 | 9.3908 | 15.6132 | 15.6424 | 7.9286 | |
|
| 2.7324 | 5.0 | 6045 | 2.5321 | 16.1222 | 9.0046 | 15.7392 | 15.813 | 8.1471 | |
|
| 2.6572 | 6.0 | 7254 | 2.5073 | 17.4735 | 10.8534 | 17.0458 | 17.0905 | 6.9538 | |
|
| 2.6118 | 7.0 | 8463 | 2.5132 | 16.6198 | 9.8078 | 16.2883 | 16.3328 | 7.2605 | |
|
| 2.5818 | 8.0 | 9672 | 2.5050 | 16.471 | 9.6857 | 16.1028 | 16.1929 | 7.4538 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.12.0.dev0 |
|
- Pytorch 1.9.1+cu111 |
|
- Datasets 1.12.2.dev0 |
|
- Tokenizers 0.10.3 |
|
|
