---
license: mit
base_model: facebook/mbart-large-50
tags:
- generated_from_trainer
model-index:
- name: models
  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. -->

# models

This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0060

## 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: 2

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 1.4786        | 0.0699 | 500   | 0.0108          |
| 0.0542        | 0.1398 | 1000  | 0.0094          |
| 0.01          | 0.2097 | 1500  | 0.0086          |
| 0.0095        | 0.2796 | 2000  | 0.0080          |
| 0.0082        | 0.3495 | 2500  | 0.0076          |
| 0.0078        | 0.4193 | 3000  | 0.0075          |
| 0.0081        | 0.4892 | 3500  | 0.0074          |
| 0.0083        | 0.5591 | 4000  | 0.0071          |
| 0.0071        | 0.6290 | 4500  | 0.0070          |
| 0.0074        | 0.6989 | 5000  | 0.0069          |
| 0.0075        | 0.7688 | 5500  | 0.0067          |
| 0.0073        | 0.8387 | 6000  | 0.0066          |
| 0.007         | 0.9086 | 6500  | 0.0065          |
| 0.0075        | 0.9785 | 7000  | 0.0064          |
| 0.006         | 1.0484 | 7500  | 0.0063          |
| 0.0181        | 1.1183 | 8000  | 0.0077          |
| 0.0066        | 1.1881 | 8500  | 0.0064          |
| 0.0067        | 1.2580 | 9000  | 0.0107          |
| 0.0087        | 1.3279 | 9500  | 0.0091          |
| 0.0065        | 1.3978 | 10000 | 0.0062          |
| 0.0054        | 1.4677 | 10500 | 0.0061          |
| 0.0055        | 1.5376 | 11000 | 0.0061          |
| 0.0053        | 1.6075 | 11500 | 0.0060          |
| 0.0052        | 1.6774 | 12000 | 0.0060          |
| 0.0051        | 1.7473 | 12500 | 0.0060          |
| 0.0051        | 1.8172 | 13000 | 0.0060          |
| 0.0063        | 1.8871 | 13500 | 0.0063          |
| 0.0054        | 1.9569 | 14000 | 0.0060          |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.19.1