---
license: mit
base_model: facebook/mbart-large-50
tags:
- generated_from_trainer
model-index:
- name: mbart-large-50-bcoqa
  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-bcoqa

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: 1.0137

## 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
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.8791        | 0.1   | 3500  | 1.7917          |
| 1.579         | 0.2   | 7000  | 1.4741          |
| 1.4918        | 0.3   | 10500 | 1.4246          |
| 1.422         | 0.4   | 14000 | 1.3369          |
| 1.4088        | 0.5   | 17500 | 1.3064          |
| 1.3245        | 0.61  | 21000 | 1.2566          |
| 1.3205        | 0.71  | 24500 | 1.2274          |
| 1.3168        | 0.81  | 28000 | 1.2052          |
| 1.2256        | 0.91  | 31500 | 1.1630          |
| 1.0668        | 1.01  | 35000 | 1.1543          |
| 1.0185        | 1.11  | 38500 | 1.1391          |
| 0.9521        | 1.21  | 42000 | 1.1076          |
| 0.9467        | 1.31  | 45500 | 1.1316          |
| 1.0128        | 1.41  | 49000 | 1.0849          |
| 0.9948        | 1.51  | 52500 | 1.0619          |
| 0.9601        | 1.61  | 56000 | 1.0489          |
| 0.9479        | 1.72  | 59500 | 1.0353          |
| 0.9046        | 1.82  | 63000 | 1.0212          |
| 0.8924        | 1.92  | 66500 | 1.0137          |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1