| --- |
| license: apache-2.0 |
| base_model: bert-base-uncased |
| tags: |
| - generated_from_trainer |
| datasets: |
| - datasets/all_binary_and_xe_ey_fae_counterfactual |
| metrics: |
| - accuracy |
| model-index: |
| - name: testing |
| results: |
| - task: |
| name: Masked Language Modeling |
| type: fill-mask |
| dataset: |
| name: datasets/all_binary_and_xe_ey_fae_counterfactual |
| type: datasets/all_binary_and_xe_ey_fae_counterfactual |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.6740440005371309 |
| --- |
| |
| <!-- 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. --> |
|
|
| # testing |
|
|
| This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the datasets/all_binary_and_xe_ey_fae_counterfactual dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.7135 |
| - Accuracy: 0.6740 |
|
|
| ## 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: 8 |
| - eval_batch_size: 8 |
| - seed: 100 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 16 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - training_steps: 10 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 2.068 | 0.0 | 5 | 1.7758 | 0.6650 | |
| | 1.9159 | 0.0 | 10 | 1.7192 | 0.6736 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.36.2 |
| - Pytorch 2.2.0+cu121 |
| - Datasets 2.17.0 |
| - Tokenizers 0.15.2 |
| |
