metadata
library_name: transformers
base_model: malmarjeh/mbert2mbert-arabic-text-summarization
tags:
- generated_from_trainer
model-index:
- name: resultmbert2mbert
results: []
resultmbert2mbert
This model is a fine-tuned version of malmarjeh/mbert2mbert-arabic-text-summarization on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8701
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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.551 | 0.4263 | 500 | 1.0592 |
| 1.1939 | 0.8525 | 1000 | 0.9787 |
| 1.0979 | 1.2788 | 1500 | 0.9425 |
| 1.0436 | 1.7050 | 2000 | 0.9134 |
| 1.0132 | 2.1313 | 2500 | 0.9038 |
| 0.9645 | 2.5575 | 3000 | 0.8905 |
| 0.9608 | 2.9838 | 3500 | 0.8857 |
| 0.9526 | 3.4101 | 4000 | 0.8931 |
| 0.96 | 3.8363 | 4500 | 0.8838 |
| 0.9254 | 4.2626 | 5000 | 0.8804 |
| 0.9023 | 4.6888 | 5500 | 0.8724 |
| 0.884 | 5.1151 | 6000 | 0.8754 |
| 0.8496 | 5.5413 | 6500 | 0.8656 |
| 0.85 | 5.9676 | 7000 | 0.8653 |
| 0.8076 | 6.3939 | 7500 | 0.8668 |
| 0.8119 | 6.8201 | 8000 | 0.8655 |
| 0.7953 | 7.2464 | 8500 | 0.8676 |
| 0.7719 | 7.6726 | 9000 | 0.8656 |
| 0.7657 | 8.0989 | 9500 | 0.8710 |
| 0.7446 | 8.5251 | 10000 | 0.8694 |
| 0.7524 | 8.9514 | 10500 | 0.8658 |
| 0.729 | 9.3777 | 11000 | 0.8699 |
| 0.7338 | 9.8039 | 11500 | 0.8701 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1