---
license: mit
base_model: october-sd/mbart-large-50-finetuned-mr-sum
tags:
- summarization
- generated_from_trainer
model-index:
- name: mbart-large-50-finetuned-mr-sum-finetuned-hindi
  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. -->

# mbart-large-50-finetuned-mr-sum-finetuned-hindi

This model is a fine-tuned version of [october-sd/mbart-large-50-finetuned-mr-sum](https://huggingface.co/october-sd/mbart-large-50-finetuned-mr-sum) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9019

## 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: 5.6e-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
- lr_scheduler_warmup_steps: 300
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.281         | 1.0   | 3905 | 1.9741          |
| 1.6731        | 2.0   | 7810 | 1.9019          |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2