---
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: 0.1239
- Accuracy: 0.9603

## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 76   | 2.1645          | 0.1921   |
| No log        | 2.0   | 152  | 1.8505          | 0.4238   |
| No log        | 3.0   | 228  | 1.4303          | 0.6887   |
| No log        | 4.0   | 304  | 1.0770          | 0.7682   |
| No log        | 5.0   | 380  | 0.8012          | 0.8477   |
| No log        | 6.0   | 456  | 0.6188          | 0.8609   |
| 1.4872        | 7.0   | 532  | 0.4291          | 0.9205   |
| 1.4872        | 8.0   | 608  | 0.3219          | 0.9338   |
| 1.4872        | 9.0   | 684  | 0.2561          | 0.9536   |
| 1.4872        | 10.0  | 760  | 0.2071          | 0.9536   |
| 1.4872        | 11.0  | 836  | 0.1758          | 0.9603   |
| 1.4872        | 12.0  | 912  | 0.1486          | 0.9603   |
| 1.4872        | 13.0  | 988  | 0.1443          | 0.9603   |
| 0.3011        | 14.0  | 1064 | 0.1384          | 0.9603   |
| 0.3011        | 15.0  | 1140 | 0.1377          | 0.9603   |
| 0.3011        | 16.0  | 1216 | 0.1347          | 0.9603   |
| 0.3011        | 17.0  | 1292 | 0.1267          | 0.9603   |
| 0.3011        | 18.0  | 1368 | 0.1223          | 0.9603   |
| 0.3011        | 19.0  | 1444 | 0.1256          | 0.9603   |
| 0.1494        | 20.0  | 1520 | 0.1239          | 0.9603   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1