---
tags:
- generated_from_trainer
datasets:
- hindi_english_machine_translation
metrics:
- bleu
model-index:
- name: mbart-large-cc25-ge-en-to-hi
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: hindi_english_machine_translation
      type: hindi_english_machine_translation
      args: hi-en
    metrics:
    - name: Bleu
      type: bleu
      value: 4.5974
---

<!-- 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. -->

# mbart-large-cc25-ge-en-to-hi

This model is a fine-tuned version of [facebook/mbart-large-cc25](https://huggingface.co/facebook/mbart-large-cc25) on the hindi_english_machine_translation dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3397
- Bleu: 4.5974
- Gen Len: 66.244

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:------:|:---------------:|:------:|:-------:|
| 1.4602        | 1.0   | 135739 | 1.3397          | 4.5974 | 66.244  |


### Framework versions

- Transformers 4.19.1
- Pytorch 1.11.0+cu102
- Datasets 1.18.0
- Tokenizers 0.12.1