ml_sum_v1
This model is a fine-tuned version of mHossain/Albaniani_sum_v1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.2080
- Rouge1: 6.9869
- Rouge2: 2.6256
- Rougel: 6.4271
- Rougelsum: 6.8073
- Gen Len: 19.0
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5000
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 312 | 2.5009 | 5.4872 | 1.8136 | 5.032 | 5.3296 | 18.985 |
| 3.2952 | 2.0 | 624 | 2.2080 | 6.9869 | 2.6256 | 6.4271 | 6.8073 | 19.0 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2