metadata
license: apache-2.0
base_model: riotu-lab/ArabianGPT-01B
tags:
- generated_from_trainer
metrics:
- bleu
- rouge
model-index:
- name: results
results: []
results
This model is a fine-tuned version of riotu-lab/ArabianGPT-01B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.9084
- Bleu: 0.3172
- Rouge1: 0.5869
- Rouge2: 0.3505
- Rougel: 0.5504
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: 8
- eval_batch_size: 8
- 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 | Bleu | Validation Loss | Rouge1 | Rouge2 | Rougel |
---|---|---|---|---|---|---|---|
3.359 | 1.5674 | 500 | 0.1142 | 3.1283 | 0.3298 | 0.0843 | 0.2561 |
2.9208 | 3.1348 | 1000 | 0.1491 | 2.7298 | 0.4041 | 0.1430 | 0.3408 |
2.619 | 4.7022 | 1500 | 0.1607 | 2.6229 | 0.4264 | 0.1631 | 0.3675 |
2.4047 | 4.3384 | 2000 | 2.2002 | 0.2721 | 0.4976 | 0.2542 | 0.4506 |
2.19 | 5.4230 | 2500 | 2.0992 | 0.2854 | 0.5205 | 0.2788 | 0.4773 |
2.0473 | 6.5076 | 3000 | 2.0362 | 0.2929 | 0.5381 | 0.2965 | 0.4965 |
1.9397 | 7.5922 | 3500 | 1.9933 | 0.2996 | 0.5494 | 0.3103 | 0.5102 |
1.857 | 8.6768 | 4000 | 1.9647 | 0.3024 | 0.5598 | 0.3191 | 0.5203 |
1.784 | 9.7614 | 4500 | 1.9443 | 0.3062 | 0.5675 | 0.3269 | 0.5279 |
1.7239 | 10.8460 | 5000 | 1.9320 | 0.3099 | 0.5724 | 0.3339 | 0.5341 |
1.6713 | 11.9306 | 5500 | 1.9206 | 0.3116 | 0.5765 | 0.3383 | 0.5387 |
1.6263 | 13.0152 | 6000 | 1.9168 | 0.3127 | 0.5781 | 0.3416 | 0.5416 |
1.5869 | 14.0998 | 6500 | 1.9148 | 0.3137 | 0.5829 | 0.3448 | 0.5451 |
1.5544 | 15.1844 | 7000 | 1.9121 | 0.3158 | 0.5845 | 0.3476 | 0.5476 |
1.5307 | 16.2690 | 7500 | 1.9106 | 0.3165 | 0.5853 | 0.3488 | 0.5486 |
1.5087 | 17.3536 | 8000 | 1.9093 | 0.3169 | 0.5861 | 0.3504 | 0.5500 |
1.4937 | 18.4382 | 8500 | 1.9084 | 0.3172 | 0.5869 | 0.3505 | 0.5504 |
1.4824 | 19.5228 | 9000 | 1.9086 | 0.3178 | 0.5876 | 0.3513 | 0.5510 |
Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1