led-risalah_data_v1
This model is a fine-tuned version of silmiaulia/led-risalah-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.2529
- Rouge1 Precision: 0.6337
- Rouge1 Recall: 0.1066
- Rouge1 Fmeasure: 0.1806
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 Precision | Rouge1 Recall | Rouge1 Fmeasure |
|---|---|---|---|---|---|---|
| 2.9308 | 0.9143 | 8 | 2.3588 | 0.5646 | 0.0934 | 0.1584 |
| 2.2677 | 1.8286 | 16 | 2.2529 | 0.6337 | 0.1066 | 0.1806 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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