---
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: 0.5597
- Accuracy: 0.9630

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 18

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 54   | 2.2273          | 0.2130   |
| No log        | 2.0   | 108  | 2.1305          | 0.3148   |
| No log        | 3.0   | 162  | 1.9882          | 0.6204   |
| No log        | 4.0   | 216  | 1.8126          | 0.6852   |
| No log        | 5.0   | 270  | 1.6344          | 0.7593   |
| No log        | 6.0   | 324  | 1.4635          | 0.8241   |
| No log        | 7.0   | 378  | 1.3043          | 0.8426   |
| No log        | 8.0   | 432  | 1.1541          | 0.8796   |
| No log        | 9.0   | 486  | 1.0312          | 0.8889   |
| 1.7754        | 10.0  | 540  | 0.9199          | 0.9074   |
| 1.7754        | 11.0  | 594  | 0.8311          | 0.9259   |
| 1.7754        | 12.0  | 648  | 0.7500          | 0.9259   |
| 1.7754        | 13.0  | 702  | 0.6884          | 0.9444   |
| 1.7754        | 14.0  | 756  | 0.6391          | 0.9444   |
| 1.7754        | 15.0  | 810  | 0.6049          | 0.9537   |
| 1.7754        | 16.0  | 864  | 0.5796          | 0.9537   |
| 1.7754        | 17.0  | 918  | 0.5652          | 0.9630   |
| 1.7754        | 18.0  | 972  | 0.5597          | 0.9630   |


### Framework versions

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