| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - Graphcore/vqa-lxmert | |
| metrics: | |
| - accuracy | |
| model-index: | |
| - name: vqa | |
| results: | |
| - task: | |
| name: Question Answering | |
| type: question-answering | |
| dataset: | |
| name: Graphcore/vqa-lxmert | |
| type: Graphcore/vqa-lxmert | |
| args: vqa | |
| metrics: | |
| - name: Accuracy | |
| type: accuracy | |
| value: 0.7242196202278137 | |
| <!-- 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. --> | |
| # vqa | |
| This model is a fine-tuned version of [unc-nlp/lxmert-base-uncased](https://huggingface.co/unc-nlp/lxmert-base-uncased) on the Graphcore/vqa-lxmert dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.0009 | |
| - Accuracy: 0.7242 | |
| ## 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: 1 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - distributed_type: IPU | |
| - total_train_batch_size: 64 | |
| - total_eval_batch_size: 128 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - lr_scheduler_warmup_ratio: 0.1 | |
| - num_epochs: 4.0 | |
| - training precision: Mixed Precision | |
| ### Training results | |
| ### Framework versions | |
| - Transformers 4.18.0.dev0 | |
| - Pytorch 1.10.0+cpu | |
| - Datasets 2.0.0 | |
| - Tokenizers 0.11.6 | |