nllb-200-distilled-1.3B-finetuned-finetuned-finetuned-finetuned
This model is a fine-tuned version of KevinKibe/nllb-200-distilled-1.3B-finetuned-finetuned-finetuned on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3966
- Rouge: 0.2713
- Gen Len: 22.5
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge | Gen Len |
---|---|---|---|---|---|
0.0032 | 200.0 | 200 | 0.4363 | 0.2835 | 22.0 |
0.0003 | 400.0 | 400 | 0.3573 | 0.2713 | 22.5 |
0.0 | 600.0 | 600 | 0.3756 | 0.2762 | 19.5 |
0.0 | 800.0 | 800 | 0.3805 | 0.2762 | 19.5 |
0.0 | 1000.0 | 1000 | 0.3809 | 0.2762 | 19.5 |
0.0 | 1200.0 | 1200 | 0.3848 | 0.2762 | 19.5 |
0.0 | 1400.0 | 1400 | 0.3964 | 0.2713 | 22.5 |
0.0 | 1600.0 | 1600 | 0.3961 | 0.2713 | 22.5 |
0.0 | 1800.0 | 1800 | 0.3964 | 0.2713 | 22.5 |
0.0 | 2000.0 | 2000 | 0.3966 | 0.2713 | 22.5 |
Framework versions
- Transformers 4.39.2
- Pytorch 2.2.2+cu121
- Datasets 2.21.0
- Tokenizers 0.15.2
- Downloads last month
- 7