File size: 2,365 Bytes
9ef8d81 |
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 |
---
tags:
- summarization
- generated_from_trainer
model-index:
- name: led-risalah_data_v7
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. -->
# led-risalah_data_v7
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8807
- Rouge1 Precision: 0.6909
- Rouge1 Recall: 0.1722
- Rouge1 Fmeasure: 0.2753
## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 Fmeasure | Rouge1 Precision | Rouge1 Recall |
|:-------------:|:-----:|:----:|:---------------:|:---------------:|:----------------:|:-------------:|
| 1.7531 | 1.0 | 70 | 1.7163 | 0.2707 | 0.6515 | 0.1714 |
| 1.4557 | 2.0 | 140 | 1.6342 | 0.2716 | 0.6745 | 0.1705 |
| 1.132 | 3.0 | 210 | 1.6420 | 0.2784 | 0.686 | 0.175 |
| 1.0552 | 4.0 | 280 | 1.6372 | 0.2828 | 0.6879 | 0.1786 |
| 1.0587 | 5.0 | 350 | 1.6587 | 0.2595 | 0.6314 | 0.1637 |
| 0.7863 | 6.0 | 420 | 1.6967 | 0.2871 | 0.7038 | 0.181 |
| 0.4577 | 7.0 | 490 | 1.7779 | 0.2717 | 0.6783 | 0.1703 |
| 0.6156 | 8.0 | 560 | 1.7964 | 0.2637 | 0.6474 | 0.1659 |
| 0.593 | 9.0 | 630 | 1.8699 | 0.2747 | 0.6797 | 0.1728 |
| 0.4265 | 10.0 | 700 | 1.8807 | 0.2753 | 0.6909 | 0.1722 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.15.1
|