---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: bert-base-uncased-finetuned-vi-infovqa
  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. -->

# bert-base-uncased-finetuned-vi-infovqa

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 13.9895

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 250500
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 4.3635        | 1.07  | 500   | 4.5286          |
| 3.8961        | 2.13  | 1000  | 4.4055          |
| 3.3012        | 3.2   | 1500  | 5.0429          |
| 2.5998        | 4.26  | 2000  | 5.4774          |
| 1.8851        | 5.33  | 2500  | 6.4376          |
| 1.3968        | 6.4   | 3000  | 6.8778          |
| 1.1244        | 7.46  | 3500  | 7.1008          |
| 0.8851        | 8.53  | 4000  | 6.8303          |
| 0.7654        | 9.59  | 4500  | 8.6628          |
| 0.6895        | 10.66 | 5000  | 6.0228          |
| 0.5989        | 11.73 | 5500  | 8.8191          |
| 0.6033        | 12.79 | 6000  | 9.7359          |
| 0.6005        | 13.86 | 6500  | 7.6668          |
| 0.522         | 14.93 | 7000  | 8.7185          |
| 0.464         | 15.99 | 7500  | 10.1035         |
| 0.4112        | 17.06 | 8000  | 8.7928          |
| 0.3501        | 18.12 | 8500  | 9.9157          |
| 0.3401        | 19.19 | 9000  | 12.1013         |
| 0.3233        | 20.26 | 9500  | 10.2730         |
| 0.2513        | 21.32 | 10000 | 8.4839          |
| 0.2319        | 22.39 | 10500 | 10.9367         |
| 0.2269        | 23.45 | 11000 | 9.6821          |
| 0.237         | 24.52 | 11500 | 10.2357         |
| 0.1868        | 25.59 | 12000 | 9.8762          |
| 0.1655        | 26.65 | 12500 | 10.7398         |
| 0.1561        | 27.72 | 13000 | 11.8157         |
| 0.1714        | 28.78 | 13500 | 10.8686         |
| 0.1098        | 29.85 | 14000 | 13.1537         |
| 0.1222        | 30.92 | 14500 | 14.5398         |
| 0.1325        | 31.98 | 15000 | 12.6095         |
| 0.1088        | 33.05 | 15500 | 12.0747         |
| 0.0855        | 34.12 | 16000 | 12.4450         |
| 0.0832        | 35.18 | 16500 | 12.9436         |
| 0.0687        | 36.25 | 17000 | 12.5902         |
| 0.0804        | 37.31 | 17500 | 11.9873         |
| 0.0427        | 38.38 | 18000 | 12.6357         |
| 0.0529        | 39.45 | 18500 | 11.5851         |
| 0.0478        | 40.51 | 19000 | 13.1796         |
| 0.0513        | 41.58 | 19500 | 13.8597         |
| 0.0449        | 42.64 | 20000 | 13.6467         |
| 0.0327        | 43.71 | 20500 | 13.0391         |
| 0.0329        | 44.78 | 21000 | 13.1984         |
| 0.0266        | 45.84 | 21500 | 13.9690         |
| 0.0301        | 46.91 | 22000 | 13.9516         |
| 0.0193        | 47.97 | 22500 | 13.9104         |
| 0.0273        | 49.04 | 23000 | 13.9895         |


### Framework versions

- Transformers 4.14.1
- Pytorch 1.10.0+cu111
- Datasets 1.16.1
- Tokenizers 0.10.3