metadata
license: cc-by-nc-4.0
base_model: facebook/nllb-200-distilled-600M
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: nllb-200-distilled-600M-finetuned_ramayana_sns_prose_lexrank_new
results: []
nllb-200-distilled-600M-finetuned_ramayana_sns_prose_lexrank_new
This model is a fine-tuned version of facebook/nllb-200-distilled-600M on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.5955
- Rouge1: 17.0715
- Rouge2: 1.7786
- Rougel: 13.4279
- Rougelsum: 15.116
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: 1e-05
- train_batch_size: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 3.8967 | 1.0 | 86 | 3.7945 | 15.1996 | 1.2821 | 12.4518 | 13.4409 |
| 3.8364 | 2.0 | 172 | 3.7584 | 15.4522 | 1.4203 | 12.6976 | 13.5883 |
| 3.8006 | 3.0 | 258 | 3.7351 | 15.6107 | 1.5487 | 12.7653 | 13.6495 |
| 3.7663 | 4.0 | 344 | 3.7081 | 15.7318 | 1.4526 | 12.9915 | 13.8208 |
| 3.7108 | 5.0 | 430 | 3.6849 | 14.9819 | 1.335 | 12.3487 | 12.9351 |
| 3.6932 | 6.0 | 516 | 3.6721 | 15.7441 | 1.3281 | 12.943 | 13.6367 |
| 3.6635 | 7.0 | 602 | 3.6599 | 15.7133 | 1.4432 | 12.6204 | 13.7309 |
| 3.6417 | 8.0 | 688 | 3.6425 | 16.0359 | 1.5975 | 13.0271 | 14.1899 |
| 3.6241 | 9.0 | 774 | 3.6298 | 16.6481 | 1.7167 | 13.266 | 14.5474 |
| 3.603 | 10.0 | 860 | 3.6209 | 16.5086 | 1.7139 | 13.059 | 14.5272 |
| 3.5692 | 11.0 | 946 | 3.6120 | 16.7846 | 1.5967 | 13.171 | 14.6977 |
| 3.5757 | 12.0 | 1032 | 3.6078 | 16.7106 | 1.7489 | 13.277 | 14.8431 |
| 3.553 | 13.0 | 1118 | 3.6010 | 17.297 | 1.7352 | 13.4176 | 15.4798 |
| 3.547 | 14.0 | 1204 | 3.5955 | 17.0715 | 1.7786 | 13.4279 | 15.116 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.0.1+cu117
- Datasets 2.19.2
- Tokenizers 0.19.1