---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-file-classifier-v1
  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. -->

# bert-file-classifier-v1

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5040
- Accuracy: 0.8621

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 73   | 2.9232          | 0.2379   |
| No log        | 2.0   | 146  | 2.3616          | 0.4103   |
| No log        | 3.0   | 219  | 1.9274          | 0.5724   |
| No log        | 4.0   | 292  | 1.6500          | 0.6793   |
| No log        | 5.0   | 365  | 1.3585          | 0.7172   |
| No log        | 6.0   | 438  | 1.1529          | 0.7448   |
| 1.8175        | 7.0   | 511  | 0.9884          | 0.7690   |
| 1.8175        | 8.0   | 584  | 0.8728          | 0.7966   |
| 1.8175        | 9.0   | 657  | 0.7990          | 0.7966   |
| 1.8175        | 10.0  | 730  | 0.7191          | 0.8379   |
| 1.8175        | 11.0  | 803  | 0.7060          | 0.8069   |
| 1.8175        | 12.0  | 876  | 0.6388          | 0.8207   |
| 1.8175        | 13.0  | 949  | 0.6215          | 0.8241   |
| 0.4201        | 14.0  | 1022 | 0.6104          | 0.8310   |
| 0.4201        | 15.0  | 1095 | 0.5726          | 0.8414   |
| 0.4201        | 16.0  | 1168 | 0.6273          | 0.8138   |
| 0.4201        | 17.0  | 1241 | 0.4878          | 0.8655   |
| 0.4201        | 18.0  | 1314 | 0.5040          | 0.8586   |
| 0.4201        | 19.0  | 1387 | 0.4873          | 0.8655   |
| 0.4201        | 20.0  | 1460 | 0.5066          | 0.8655   |
| 0.1063        | 21.0  | 1533 | 0.5139          | 0.8690   |
| 0.1063        | 22.0  | 1606 | 0.5060          | 0.8655   |
| 0.1063        | 23.0  | 1679 | 0.4933          | 0.8690   |
| 0.1063        | 24.0  | 1752 | 0.5140          | 0.8690   |
| 0.1063        | 25.0  | 1825 | 0.5040          | 0.8621   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1