---
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: 2.5873
- Accuracy: 0.1544

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2.5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.6964        | 0.16  | 60   | 2.6756          | 0.0834   |
| 2.6947        | 0.31  | 120  | 2.6670          | 0.0947   |
| 2.6716        | 0.47  | 180  | 2.6428          | 0.1139   |
| 2.6315        | 0.63  | 240  | 2.6252          | 0.1268   |
| 2.6113        | 0.79  | 300  | 2.6205          | 0.1310   |
| 2.5936        | 0.94  | 360  | 2.6137          | 0.1293   |
| 2.5298        | 1.1   | 420  | 2.6065          | 0.1381   |
| 2.4691        | 1.26  | 480  | 2.6097          | 0.1452   |
| 2.4645        | 1.42  | 540  | 2.6015          | 0.1519   |
| 2.4404        | 1.57  | 600  | 2.5912          | 0.1414   |
| 2.4435        | 1.73  | 660  | 2.5890          | 0.1464   |
| 2.4425        | 1.89  | 720  | 2.5928          | 0.1514   |
| 2.4038        | 2.05  | 780  | 2.5880          | 0.1481   |
| 2.2601        | 2.2   | 840  | 2.5941          | 0.1423   |
| 2.2858        | 2.36  | 900  | 2.5873          | 0.1544   |


### Framework versions

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