---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: FineTuned-hindi-to-english-V8
  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-V8

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: 1.4699
- Rouge1: 77.4859
- Rouge2: 54.5463
- Rougel: 70.7586
- Rougelsum: 72.9591
- Gen Len: 80.2678

## 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: 14
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 3.2542        | 1.0   | 750   | 2.4128          | 66.5333 | 38.7744 | 58.3682 | 61.5066   | 77.9543 |
| 2.2929        | 2.0   | 1500  | 2.0835          | 70.0324 | 43.5622 | 62.3036 | 65.2299   | 79.0161 |
| 2.0351        | 3.0   | 2250  | 1.8982          | 72.069  | 46.4931 | 64.6929 | 67.3732   | 80.1859 |
| 1.7712        | 4.0   | 3000  | 1.7791          | 73.5869 | 48.6666 | 66.3649 | 68.8242   | 79.9375 |
| 1.6431        | 5.0   | 3750  | 1.6935          | 74.5655 | 50.0947 | 67.4126 | 69.8943   | 80.2959 |
| 1.4994        | 6.0   | 4500  | 1.6316          | 75.3132 | 51.2895 | 68.3122 | 70.7019   | 80.1347 |
| 1.4154        | 7.0   | 5250  | 1.5856          | 75.9486 | 52.1892 | 69.0828 | 71.4087   | 80.0847 |
| 1.333         | 8.0   | 6000  | 1.5516          | 76.2849 | 52.724  | 69.4646 | 71.7547   | 80.0536 |
| 1.2793        | 9.0   | 6750  | 1.5234          | 76.7711 | 53.4504 | 69.9626 | 72.215    | 80.2093 |
| 1.2219        | 10.0  | 7500  | 1.5043          | 76.9627 | 53.7785 | 70.2119 | 72.4254   | 80.1563 |
| 1.196         | 11.0  | 8250  | 1.4870          | 77.2081 | 54.1476 | 70.4764 | 72.681    | 80.4921 |
| 1.1612        | 12.0  | 9000  | 1.4771          | 77.4156 | 54.445  | 70.7305 | 72.9198   | 80.2194 |
| 1.1388        | 13.0  | 9750  | 1.4715          | 77.4179 | 54.4518 | 70.6541 | 72.8583   | 80.2815 |
| 1.1277        | 14.0  | 10500 | 1.4699          | 77.4859 | 54.5463 | 70.7586 | 72.9591   | 80.2678 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2