res_nw_dj_aragpt2-large
This model is a fine-tuned version of aubmindlab/aragpt2-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0718
- Bleu: 0.1063
- Rouge1: 0.4552
- Rouge2: 0.2232
- Rougel: 0.4516
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: 4
- eval_batch_size: 4
- 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: 20.0
Training results
Training Loss | Epoch | Step | Validation Loss | Bleu | Rouge1 | Rouge2 | Rougel |
---|---|---|---|---|---|---|---|
0.1323 | 1.0 | 5358 | 0.0757 | 0.0830 | 0.4072 | 0.1825 | 0.4035 |
0.0662 | 2.0 | 10716 | 0.0718 | 0.1063 | 0.4552 | 0.2232 | 0.4516 |
0.0526 | 3.0 | 16074 | 0.0727 | 0.1197 | 0.4753 | 0.2520 | 0.4719 |
0.0414 | 4.0 | 21432 | 0.0757 | 0.1274 | 0.4894 | 0.2644 | 0.4862 |
0.0325 | 5.0 | 26790 | 0.0819 | 0.1290 | 0.4910 | 0.2671 | 0.4875 |
0.0262 | 6.0 | 32148 | 0.0863 | 0.1297 | 0.4922 | 0.2665 | 0.4888 |
0.0221 | 7.0 | 37506 | 0.0930 | 0.1326 | 0.4960 | 0.2713 | 0.4923 |
Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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aubmindlab/aragpt2-large