File size: 2,642 Bytes
3ed6e74 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 |
---
tags:
- summarization
- ar
- Abstractive Summarization
- generated_from_trainer
datasets:
- wiki_lingua
model-index:
- name: AraT5-base-finetune-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. -->
# AraT5-base-finetune-ar-wikilingua
This model is a fine-tuned version of [UBC-NLP/AraT5-base](https://huggingface.co/UBC-NLP/AraT5-base) on the wiki_lingua dataset.
It achieves the following results on the evaluation set:
- Loss: 4.6110
- Rouge-1: 19.97
- Rouge-2: 6.9
- Rouge-l: 18.25
- Gen Len: 18.45
- Bertscore: 69.44
## 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: 0.0005
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- num_epochs: 10
- label_smoothing_factor: 0.1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Bertscore |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|
| 11.5412 | 1.0 | 312 | 6.8825 | 5.2 | 0.69 | 5.04 | 19.0 | 63.2 |
| 6.5212 | 2.0 | 624 | 5.8992 | 8.89 | 1.4 | 8.36 | 17.92 | 63.9 |
| 5.8302 | 3.0 | 936 | 5.3712 | 9.99 | 2.21 | 9.54 | 15.87 | 65.08 |
| 5.406 | 4.0 | 1248 | 5.0632 | 13.94 | 3.5 | 13.0 | 15.95 | 66.83 |
| 5.1109 | 5.0 | 1560 | 4.8718 | 15.28 | 4.34 | 14.27 | 18.26 | 66.83 |
| 4.9004 | 6.0 | 1872 | 4.7631 | 16.65 | 4.92 | 15.46 | 17.73 | 67.75 |
| 4.754 | 7.0 | 2184 | 4.6920 | 18.31 | 5.79 | 16.9 | 18.17 | 68.55 |
| 4.6369 | 8.0 | 2496 | 4.6459 | 18.6 | 6.12 | 17.16 | 18.16 | 68.66 |
| 4.5595 | 9.0 | 2808 | 4.6153 | 18.94 | 6.1 | 17.39 | 17.82 | 68.99 |
| 4.4967 | 10.0 | 3120 | 4.6110 | 19.15 | 6.25 | 17.55 | 17.91 | 69.09 |
### Framework versions
- Transformers 4.19.4
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
|