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
results: []
nllb-200-distilled-600M-finetuned_ramayana_sns_prose
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: 3.5584
- Rouge1: 19.8304
- Rouge2: 2.4248
- Rougel: 13.9446
- Rougelsum: 18.3552
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: 5.6e-06
- train_batch_size: 1
- eval_batch_size: 1
- 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 |
---|---|---|---|---|---|---|---|
4.595 | 1.0 | 427 | 4.1428 | 15.776 | 1.4778 | 12.3256 | 14.3476 |
4.1875 | 2.0 | 854 | 3.9597 | 16.6403 | 1.7896 | 12.7134 | 15.0805 |
4.0304 | 3.0 | 1281 | 3.8653 | 16.6812 | 1.8152 | 12.5282 | 15.1217 |
3.9243 | 4.0 | 1708 | 3.7984 | 17.1533 | 1.788 | 13.1478 | 15.5023 |
3.8485 | 5.0 | 2135 | 3.7505 | 17.3886 | 1.8682 | 13.1805 | 15.711 |
3.786 | 6.0 | 2562 | 3.7141 | 17.7897 | 1.9953 | 13.2044 | 15.9314 |
3.732 | 7.0 | 2989 | 3.6815 | 18.3797 | 2.0735 | 13.8603 | 16.7243 |
3.6865 | 8.0 | 3416 | 3.6559 | 18.2702 | 2.0286 | 13.3494 | 16.5957 |
3.6515 | 9.0 | 3843 | 3.6354 | 18.0194 | 1.9282 | 12.9295 | 16.4714 |
3.6177 | 10.0 | 4270 | 3.6193 | 18.7825 | 2.0085 | 13.2207 | 17.1223 |
3.5877 | 11.0 | 4697 | 3.6030 | 19.1192 | 2.1276 | 13.9442 | 17.609 |
3.5665 | 12.0 | 5124 | 3.5943 | 19.5031 | 2.3146 | 13.7631 | 17.9879 |
3.5454 | 13.0 | 5551 | 3.5828 | 19.7688 | 2.2574 | 13.9943 | 18.2914 |
3.5247 | 14.0 | 5978 | 3.5763 | 19.4478 | 2.3024 | 13.8854 | 17.9616 |
3.509 | 15.0 | 6405 | 3.5704 | 19.3998 | 2.2633 | 13.707 | 17.9534 |
3.4983 | 16.0 | 6832 | 3.5646 | 19.6401 | 2.3265 | 13.9141 | 18.2001 |
3.4865 | 17.0 | 7259 | 3.5604 | 19.1833 | 2.398 | 13.6566 | 17.7596 |
3.4802 | 18.0 | 7686 | 3.5584 | 19.8304 | 2.4248 | 13.9446 | 18.3552 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.0.1+cu117
- Datasets 2.19.2
- Tokenizers 0.19.1