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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_lexrank_new |
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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_lexrank_new |
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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: 3.5955 |
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- Rouge1: 17.0715 |
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- Rouge2: 1.7786 |
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- Rougel: 13.4279 |
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- Rougelsum: 15.116 |
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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: 1e-05 |
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- train_batch_size: 5 |
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- eval_batch_size: 5 |
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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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| 3.8967 | 1.0 | 86 | 3.7945 | 15.1996 | 1.2821 | 12.4518 | 13.4409 | |
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| 3.8364 | 2.0 | 172 | 3.7584 | 15.4522 | 1.4203 | 12.6976 | 13.5883 | |
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| 3.8006 | 3.0 | 258 | 3.7351 | 15.6107 | 1.5487 | 12.7653 | 13.6495 | |
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| 3.7663 | 4.0 | 344 | 3.7081 | 15.7318 | 1.4526 | 12.9915 | 13.8208 | |
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| 3.7108 | 5.0 | 430 | 3.6849 | 14.9819 | 1.335 | 12.3487 | 12.9351 | |
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| 3.6932 | 6.0 | 516 | 3.6721 | 15.7441 | 1.3281 | 12.943 | 13.6367 | |
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| 3.6635 | 7.0 | 602 | 3.6599 | 15.7133 | 1.4432 | 12.6204 | 13.7309 | |
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| 3.6417 | 8.0 | 688 | 3.6425 | 16.0359 | 1.5975 | 13.0271 | 14.1899 | |
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| 3.6241 | 9.0 | 774 | 3.6298 | 16.6481 | 1.7167 | 13.266 | 14.5474 | |
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| 3.603 | 10.0 | 860 | 3.6209 | 16.5086 | 1.7139 | 13.059 | 14.5272 | |
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| 3.5692 | 11.0 | 946 | 3.6120 | 16.7846 | 1.5967 | 13.171 | 14.6977 | |
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| 3.5757 | 12.0 | 1032 | 3.6078 | 16.7106 | 1.7489 | 13.277 | 14.8431 | |
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| 3.553 | 13.0 | 1118 | 3.6010 | 17.297 | 1.7352 | 13.4176 | 15.4798 | |
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| 3.547 | 14.0 | 1204 | 3.5955 | 17.0715 | 1.7786 | 13.4279 | 15.116 | |
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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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