readme: ---
  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
  