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--- |
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license: cc-by-nc-4.0 |
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base_model: facebook/nllb-200-distilled-600M |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: nllb-200-distilled-600M-finetuned_ramayana_sns_prose |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# nllb-200-distilled-600M-finetuned_ramayana_sns_prose |
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This model is a fine-tuned version of [facebook/nllb-200-distilled-600M](https://huggingface.co/facebook/nllb-200-distilled-600M) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.5584 |
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- Rouge1: 19.8304 |
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- Rouge2: 2.4248 |
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- Rougel: 13.9446 |
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- Rougelsum: 18.3552 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5.6e-06 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:| |
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| 4.595 | 1.0 | 427 | 4.1428 | 15.776 | 1.4778 | 12.3256 | 14.3476 | |
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| 4.1875 | 2.0 | 854 | 3.9597 | 16.6403 | 1.7896 | 12.7134 | 15.0805 | |
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| 4.0304 | 3.0 | 1281 | 3.8653 | 16.6812 | 1.8152 | 12.5282 | 15.1217 | |
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| 3.9243 | 4.0 | 1708 | 3.7984 | 17.1533 | 1.788 | 13.1478 | 15.5023 | |
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| 3.8485 | 5.0 | 2135 | 3.7505 | 17.3886 | 1.8682 | 13.1805 | 15.711 | |
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| 3.786 | 6.0 | 2562 | 3.7141 | 17.7897 | 1.9953 | 13.2044 | 15.9314 | |
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| 3.732 | 7.0 | 2989 | 3.6815 | 18.3797 | 2.0735 | 13.8603 | 16.7243 | |
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| 3.6865 | 8.0 | 3416 | 3.6559 | 18.2702 | 2.0286 | 13.3494 | 16.5957 | |
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| 3.6515 | 9.0 | 3843 | 3.6354 | 18.0194 | 1.9282 | 12.9295 | 16.4714 | |
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| 3.6177 | 10.0 | 4270 | 3.6193 | 18.7825 | 2.0085 | 13.2207 | 17.1223 | |
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| 3.5877 | 11.0 | 4697 | 3.6030 | 19.1192 | 2.1276 | 13.9442 | 17.609 | |
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| 3.5665 | 12.0 | 5124 | 3.5943 | 19.5031 | 2.3146 | 13.7631 | 17.9879 | |
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| 3.5454 | 13.0 | 5551 | 3.5828 | 19.7688 | 2.2574 | 13.9943 | 18.2914 | |
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| 3.5247 | 14.0 | 5978 | 3.5763 | 19.4478 | 2.3024 | 13.8854 | 17.9616 | |
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| 3.509 | 15.0 | 6405 | 3.5704 | 19.3998 | 2.2633 | 13.707 | 17.9534 | |
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| 3.4983 | 16.0 | 6832 | 3.5646 | 19.6401 | 2.3265 | 13.9141 | 18.2001 | |
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| 3.4865 | 17.0 | 7259 | 3.5604 | 19.1833 | 2.398 | 13.6566 | 17.7596 | |
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| 3.4802 | 18.0 | 7686 | 3.5584 | 19.8304 | 2.4248 | 13.9446 | 18.3552 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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