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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: Finetuned-hindi-to-english-V5
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Finetuned-hindi-to-english-V5
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.
It achieves the following results on the evaluation set:
- Loss: 3.3700
- Rouge1: 46.8571
- Rouge2: 20.4177
- Rougel: 41.8681
- Rougelsum: 41.979
- Gen Len: 25.9805
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 3.9003 | 1.0 | 500 | 3.5309 | 44.7687 | 19.3162 | 39.7482 | 39.8743 | 47.273 |
| 3.3953 | 2.0 | 1000 | 3.4295 | 45.583 | 19.7519 | 40.5147 | 40.6327 | 31.2255 |
| 3.1149 | 3.0 | 1500 | 3.3829 | 45.9163 | 19.8789 | 41.0229 | 41.1501 | 34.532 |
| 2.9111 | 4.0 | 2000 | 3.3663 | 45.9453 | 19.9925 | 41.0019 | 41.1038 | 32.6625 |
| 2.7429 | 5.0 | 2500 | 3.3609 | 46.2821 | 20.1008 | 41.2762 | 41.389 | 29.1325 |
| 2.6212 | 6.0 | 3000 | 3.3592 | 46.3719 | 20.2255 | 41.2826 | 41.4093 | 28.0275 |
| 2.5156 | 7.0 | 3500 | 3.3632 | 46.5546 | 20.3336 | 41.5246 | 41.627 | 25.3715 |
| 2.4429 | 8.0 | 4000 | 3.3646 | 46.5347 | 20.2066 | 41.5536 | 41.6628 | 27.2935 |
| 2.3909 | 9.0 | 4500 | 3.3689 | 46.9327 | 20.3823 | 41.8767 | 41.9965 | 25.751 |
| 2.358 | 10.0 | 5000 | 3.3700 | 46.8571 | 20.4177 | 41.8681 | 41.979 | 25.9805 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
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