| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: interview_classifier |
| 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. --> |
|
|
| # interview_classifier |
| |
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 2.0881 |
| - Accuracy: 0.2593 |
| |
| ## 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: 1e-05 |
| - train_batch_size: 2 |
| - eval_batch_size: 2 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | No log | 1.0 | 54 | 2.2885 | 0.1481 | |
| | No log | 2.0 | 108 | 2.2611 | 0.1481 | |
| | No log | 3.0 | 162 | 2.2186 | 0.2593 | |
| | No log | 4.0 | 216 | 2.1877 | 0.2222 | |
| | No log | 5.0 | 270 | 2.1593 | 0.2593 | |
| | No log | 6.0 | 324 | 2.1332 | 0.2593 | |
| | No log | 7.0 | 378 | 2.1185 | 0.2963 | |
| | No log | 8.0 | 432 | 2.0965 | 0.2593 | |
| | No log | 9.0 | 486 | 2.0914 | 0.2593 | |
| | 1.9418 | 10.0 | 540 | 2.0881 | 0.2593 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.47.1 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.2.0 |
| - Tokenizers 0.21.0 |
| |
