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---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased-finetuned-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. -->
# distilbert-base-uncased-finetuned-infovqa
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8872
## 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: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log | 0.02 | 100 | 4.7706 |
| No log | 0.05 | 200 | 4.4399 |
| No log | 0.07 | 300 | 3.8175 |
| No log | 0.09 | 400 | 3.8306 |
| 3.3071 | 0.12 | 500 | 3.6480 |
| 3.3071 | 0.14 | 600 | 3.6451 |
| 3.3071 | 0.16 | 700 | 3.4974 |
| 3.3071 | 0.19 | 800 | 3.4686 |
| 3.3071 | 0.21 | 900 | 3.4703 |
| 3.5336 | 0.23 | 1000 | 3.3165 |
| 3.5336 | 0.25 | 1100 | 3.3634 |
| 3.5336 | 0.28 | 1200 | 3.3466 |
| 3.5336 | 0.3 | 1300 | 3.3411 |
| 3.5336 | 0.32 | 1400 | 3.2456 |
| 3.3593 | 0.35 | 1500 | 3.3257 |
| 3.3593 | 0.37 | 1600 | 3.2941 |
| 3.3593 | 0.39 | 1700 | 3.2581 |
| 3.3593 | 0.42 | 1800 | 3.1680 |
| 3.3593 | 0.44 | 1900 | 3.2077 |
| 3.2436 | 0.46 | 2000 | 3.2422 |
| 3.2436 | 0.49 | 2100 | 3.2529 |
| 3.2436 | 0.51 | 2200 | 3.2681 |
| 3.2436 | 0.53 | 2300 | 3.1055 |
| 3.2436 | 0.56 | 2400 | 3.0174 |
| 3.093 | 0.58 | 2500 | 3.0608 |
| 3.093 | 0.6 | 2600 | 3.0200 |
| 3.093 | 0.63 | 2700 | 2.9884 |
| 3.093 | 0.65 | 2800 | 3.0041 |
| 3.093 | 0.67 | 2900 | 2.9700 |
| 3.0087 | 0.69 | 3000 | 3.0993 |
| 3.0087 | 0.72 | 3100 | 3.0499 |
| 3.0087 | 0.74 | 3200 | 2.9317 |
| 3.0087 | 0.76 | 3300 | 3.0817 |
| 3.0087 | 0.79 | 3400 | 3.0035 |
| 2.9694 | 0.81 | 3500 | 3.0850 |
| 2.9694 | 0.83 | 3600 | 2.9948 |
| 2.9694 | 0.86 | 3700 | 2.9874 |
| 2.9694 | 0.88 | 3800 | 2.9202 |
| 2.9694 | 0.9 | 3900 | 2.9322 |
| 2.8277 | 0.93 | 4000 | 2.9195 |
| 2.8277 | 0.95 | 4100 | 2.8638 |
| 2.8277 | 0.97 | 4200 | 2.8809 |
| 2.8277 | 1.0 | 4300 | 2.8872 |
### Framework versions
- Transformers 4.11.3
- Pytorch 1.9.0+cu111
- Datasets 1.14.0
- Tokenizers 0.10.3
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