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--- |
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license: apache-2.0 |
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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: Finetuned-hindi-to-english-V5 |
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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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# Finetuned-hindi-to-english-V5 |
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This model is a fine-tuned version of [Helsinki-NLP/opus-mt-hi-en](https://huggingface.co/Helsinki-NLP/opus-mt-hi-en) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.3700 |
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- Rouge1: 46.8571 |
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- Rouge2: 20.4177 |
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- Rougel: 41.8681 |
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- Rougelsum: 41.979 |
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- Gen Len: 25.9805 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 10 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
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| 3.9003 | 1.0 | 500 | 3.5309 | 44.7687 | 19.3162 | 39.7482 | 39.8743 | 47.273 | |
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| 3.3953 | 2.0 | 1000 | 3.4295 | 45.583 | 19.7519 | 40.5147 | 40.6327 | 31.2255 | |
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| 3.1149 | 3.0 | 1500 | 3.3829 | 45.9163 | 19.8789 | 41.0229 | 41.1501 | 34.532 | |
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| 2.9111 | 4.0 | 2000 | 3.3663 | 45.9453 | 19.9925 | 41.0019 | 41.1038 | 32.6625 | |
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| 2.7429 | 5.0 | 2500 | 3.3609 | 46.2821 | 20.1008 | 41.2762 | 41.389 | 29.1325 | |
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| 2.6212 | 6.0 | 3000 | 3.3592 | 46.3719 | 20.2255 | 41.2826 | 41.4093 | 28.0275 | |
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| 2.5156 | 7.0 | 3500 | 3.3632 | 46.5546 | 20.3336 | 41.5246 | 41.627 | 25.3715 | |
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| 2.4429 | 8.0 | 4000 | 3.3646 | 46.5347 | 20.2066 | 41.5536 | 41.6628 | 27.2935 | |
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| 2.3909 | 9.0 | 4500 | 3.3689 | 46.9327 | 20.3823 | 41.8767 | 41.9965 | 25.751 | |
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| 2.358 | 10.0 | 5000 | 3.3700 | 46.8571 | 20.4177 | 41.8681 | 41.979 | 25.9805 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.9.0 |
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- Tokenizers 0.13.2 |
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