---
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
  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

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: 1.9896

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.5989        | 1.0   | 3605 | 1.9562          |
| 1.1384        | 2.0   | 7210 | 1.9896          |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.15.0
- Tokenizers 0.15.2