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nllb-200-distilled-600M-finetuned_ramayana_sns

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update model card README.md

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@@ -16,11 +16,11 @@ should probably proofread and complete it, then remove this comment. -->
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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: 3.4244
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- - Rouge1: 20.1343
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- - Rouge2: 2.1455
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- - Rougel: 14.6013
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- - Rougelsum: 18.4962
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  ## Model description
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@@ -45,21 +45,42 @@ The following hyperparameters were used during training:
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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: 4
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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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- | 3.9684 | 1.0 | 428 | 3.5950 | 17.6091 | 1.7385 | 13.8602 | 16.247 |
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- | 3.5 | 2.0 | 856 | 3.4845 | 18.2092 | 2.0563 | 13.2716 | 16.6222 |
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- | 3.2888 | 3.0 | 1284 | 3.4325 | 19.4156 | 2.0493 | 14.266 | 17.769 |
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- | 3.1682 | 4.0 | 1712 | 3.4244 | 20.1343 | 2.1455 | 14.6013 | 18.4962 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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  - Transformers 4.28.0
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- - Pytorch 2.0.1+cu118
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  - Datasets 2.14.4
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  - Tokenizers 0.13.3
 
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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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  - 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