|
--- |
|
license: apache-2.0 |
|
tags: |
|
- summarization |
|
- generated_from_trainer |
|
datasets: |
|
- wiki_lingua |
|
model-index: |
|
- name: mt5-base-finetuned-ar-wikilingua |
|
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-base-finetuned-ar-wikilingua |
|
|
|
This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the wiki_lingua dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 3.6790 |
|
- Rouge-1: 19.46 |
|
- Rouge-2: 6.82 |
|
- Rouge-l: 17.57 |
|
- Gen Len: 18.83 |
|
- Bertscore: 70.18 |
|
|
|
## 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: 5e-05 |
|
- train_batch_size: 4 |
|
- eval_batch_size: 4 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 250 |
|
- num_epochs: 8 |
|
- label_smoothing_factor: 0.1 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Bertscore | |
|
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:| |
|
| 4.9783 | 1.0 | 5111 | 4.0107 | 15.8 | 4.65 | 14.18 | 18.98 | 68.66 | |
|
| 4.2093 | 2.0 | 10222 | 3.8664 | 16.46 | 5.17 | 15.08 | 18.91 | 68.5 | |
|
| 4.0303 | 3.0 | 15333 | 3.7847 | 17.0 | 5.43 | 15.45 | 18.89 | 68.75 | |
|
| 3.9165 | 4.0 | 20444 | 3.7405 | 17.03 | 5.5 | 15.45 | 18.86 | 68.78 | |
|
| 3.8396 | 5.0 | 25555 | 3.7102 | 17.14 | 5.57 | 15.48 | 18.87 | 68.92 | |
|
| 3.7825 | 6.0 | 30666 | 3.6944 | 17.64 | 5.73 | 15.96 | 18.82 | 69.14 | |
|
| 3.7447 | 7.0 | 35777 | 3.6801 | 17.6 | 5.66 | 15.9 | 18.78 | 69.23 | |
|
| 3.7203 | 8.0 | 40888 | 3.6790 | 17.94 | 5.81 | 16.21 | 18.81 | 69.29 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.18.0 |
|
- Pytorch 1.10.0+cu111 |
|
- Datasets 2.1.0 |
|
- Tokenizers 0.12.1 |
|
|
