led-risalah_data_v11
This model is a fine-tuned version of silmi224/finetune-led-35000 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6843
- Rouge1 Precision: 0.7035
- Rouge1 Recall: 0.1205
- Rouge1 Fmeasure: 0.2038
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: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 Precision | Rouge1 Recall | Rouge1 Fmeasure |
|---|---|---|---|---|---|---|
| 2.6071 | 0.9714 | 17 | 1.8938 | 0.6021 | 0.1074 | 0.1803 |
| 1.745 | 2.0 | 35 | 1.7661 | 0.7095 | 0.1174 | 0.1994 |
| 1.5717 | 2.9714 | 52 | 1.7251 | 0.6704 | 0.1176 | 0.1968 |
| 1.4921 | 4.0 | 70 | 1.6772 | 0.7014 | 0.1175 | 0.1986 |
| 1.3932 | 4.9714 | 87 | 1.6745 | 0.7008 | 0.1187 | 0.2011 |
| 1.3002 | 6.0 | 105 | 1.6869 | 0.6913 | 0.1196 | 0.2012 |
| 1.2784 | 6.9714 | 122 | 1.6857 | 0.7114 | 0.1246 | 0.2097 |
| 1.1779 | 7.7714 | 136 | 1.6843 | 0.7035 | 0.1205 | 0.2038 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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Base model
silmi224/finetune-led-35000