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mbert_5_30_000
This model is a fine-tuned version of malmarjeh/mbert2mbert-arabic-text-summarization on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2958
- Rouge1: 10.0933
- Rouge2: 4.1011
- Rougel: 10.1123
- Rougelsum: 10.142
- Gen Len: 41.2852
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: 2e-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
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 0.3149 | 1.0 | 1676 | 0.2958 | 10.0933 | 4.1011 | 10.1123 | 10.142 | 41.2852 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3
