metadata
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: interview_classifier
results: []
interview_classifier
This model is a fine-tuned version of 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