---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: office-character
  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. -->

# office-character

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: 2.3380
- Accuracy: 0.3293

## 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: 3.3e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2896        | 0.09  | 200  | 2.3458          | 0.328    |
| 2.3881        | 0.18  | 400  | 2.3456          | 0.3207   |
| 2.3149        | 0.27  | 600  | 2.3552          | 0.3283   |
| 2.2579        | 0.36  | 800  | 2.3468          | 0.327    |
| 2.3016        | 0.45  | 1000 | 2.3512          | 0.327    |
| 2.3923        | 0.54  | 1200 | 2.3410          | 0.3313   |
| 2.3458        | 0.63  | 1400 | 2.3416          | 0.328    |
| 2.3522        | 0.72  | 1600 | 2.3303          | 0.3287   |
| 2.2485        | 0.81  | 1800 | 2.3291          | 0.3343   |
| 2.3083        | 0.9   | 2000 | 2.3289          | 0.3327   |
| 2.2594        | 0.99  | 2200 | 2.3336          | 0.3387   |
| 2.229         | 1.08  | 2400 | 2.3446          | 0.3213   |
| 2.3017        | 1.17  | 2600 | 2.3362          | 0.3327   |
| 2.2405        | 1.26  | 2800 | 2.3299          | 0.335    |
| 2.3291        | 1.35  | 3000 | 2.3291          | 0.33     |
| 2.2518        | 1.43  | 3200 | 2.3363          | 0.3297   |
| 2.268         | 1.52  | 3400 | 2.3623          | 0.3187   |
| 2.3198        | 1.61  | 3600 | 2.3480          | 0.3277   |
| 2.1873        | 1.7   | 3800 | 2.3355          | 0.3293   |
| 2.2634        | 1.79  | 4000 | 2.3291          | 0.326    |
| 2.1011        | 1.88  | 4200 | 2.3345          | 0.333    |
| 2.1965        | 1.97  | 4400 | 2.3383          | 0.3293   |
| 2.2368        | 2.06  | 4600 | 2.3320          | 0.329    |
| 2.2226        | 2.15  | 4800 | 2.3453          | 0.3263   |
| 2.2354        | 2.24  | 5000 | 2.3372          | 0.33     |
| 2.2829        | 2.33  | 5200 | 2.3547          | 0.3223   |
| 2.1544        | 2.42  | 5400 | 2.3336          | 0.3287   |
| 2.2777        | 2.51  | 5600 | 2.3425          | 0.3283   |
| 2.0763        | 2.6   | 5800 | 2.3339          | 0.3307   |
| 2.2738        | 2.69  | 6000 | 2.3389          | 0.3293   |
| 2.1013        | 2.78  | 6200 | 2.3411          | 0.327    |
| 2.1058        | 2.87  | 6400 | 2.3357          | 0.332    |
| 2.1621        | 2.96  | 6600 | 2.3380          | 0.3293   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.14.4
- Tokenizers 0.13.3