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--- |
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license: cc-by-nc-4.0 |
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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 |
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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 |
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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: 1.1052 |
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- Rouge1: 37.2964 |
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- Rouge2: 13.3703 |
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- Rougel: 22.7017 |
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- Rougelsum: 35.5842 |
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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-05 |
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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: 25 |
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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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| 3.9959 | 1.0 | 427 | 3.4147 | 17.2457 | 1.4651 | 13.9187 | 15.2006 | |
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| 3.5248 | 2.0 | 854 | 3.1330 | 16.7103 | 1.5796 | 13.8012 | 15.1218 | |
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| 3.2806 | 3.0 | 1281 | 2.9159 | 19.8896 | 2.3058 | 15.4336 | 18.1143 | |
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| 3.0859 | 4.0 | 1708 | 2.7715 | 22.584 | 3.1418 | 15.1369 | 20.8655 | |
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| 2.9227 | 5.0 | 2135 | 2.5706 | 22.2583 | 3.0743 | 15.4466 | 20.6234 | |
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| 2.7698 | 6.0 | 2562 | 2.4091 | 24.7108 | 3.5182 | 16.0307 | 22.8396 | |
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| 2.6318 | 7.0 | 2989 | 2.2848 | 24.8276 | 4.0799 | 16.1394 | 22.995 | |
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| 2.5055 | 8.0 | 3416 | 2.1317 | 26.6203 | 4.5536 | 16.398 | 24.9144 | |
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| 2.3865 | 9.0 | 3843 | 2.0097 | 27.2979 | 4.6529 | 16.5061 | 25.4136 | |
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| 2.2735 | 10.0 | 4270 | 1.8829 | 26.8753 | 4.8247 | 16.5212 | 25.2001 | |
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| 2.1712 | 11.0 | 4697 | 1.7707 | 28.2474 | 5.3564 | 16.143 | 26.4664 | |
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| 2.0894 | 12.0 | 5124 | 1.6892 | 28.8711 | 6.1654 | 16.6789 | 27.1269 | |
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| 2.0222 | 13.0 | 5551 | 1.6208 | 30.2457 | 6.9935 | 17.3494 | 28.5843 | |
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| 1.9587 | 14.0 | 5978 | 1.5326 | 30.7249 | 7.2678 | 17.8036 | 28.8945 | |
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| 1.8861 | 15.0 | 6405 | 1.4747 | 30.5734 | 7.558 | 17.9432 | 28.7896 | |
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| 1.8268 | 16.0 | 6832 | 1.4016 | 32.3279 | 9.0045 | 19.0847 | 30.4151 | |
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| 1.7727 | 17.0 | 7259 | 1.3328 | 33.7324 | 10.4921 | 20.0239 | 32.0321 | |
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| 1.7221 | 18.0 | 7686 | 1.2880 | 34.4832 | 9.9756 | 20.3859 | 32.6687 | |
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| 1.6775 | 19.0 | 8113 | 1.2399 | 34.9426 | 10.6686 | 20.4836 | 32.9811 | |
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| 1.6392 | 20.0 | 8540 | 1.1963 | 35.0751 | 11.6233 | 21.0831 | 33.2466 | |
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| 1.6007 | 21.0 | 8967 | 1.1644 | 35.6344 | 11.9175 | 21.4471 | 33.9996 | |
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| 1.5707 | 22.0 | 9394 | 1.1438 | 35.5101 | 12.1179 | 21.2347 | 33.7518 | |
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| 1.55 | 23.0 | 9821 | 1.1182 | 37.1233 | 12.7533 | 22.4229 | 35.3803 | |
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| 1.5352 | 24.0 | 10248 | 1.1108 | 36.959 | 13.4712 | 22.9926 | 35.4021 | |
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| 1.5201 | 25.0 | 10675 | 1.1052 | 37.2964 | 13.3703 | 22.7017 | 35.5842 | |
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### Framework versions |
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- Transformers 4.28.0 |
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- Pytorch 1.12.1 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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