---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-topic-model
  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. -->

# distilbert-base-uncased-finetuned-topic-model

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2697
- Accuracy: 0.6030
- F1: 0.5963

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 2.7083        | 1.0   | 97   | 2.3146          | 0.4470   | 0.3978 |
| 1.9763        | 2.0   | 194  | 1.7865          | 0.5136   | 0.4576 |
| 1.5486        | 3.0   | 291  | 1.5441          | 0.5561   | 0.5263 |
| 1.2422        | 4.0   | 388  | 1.4228          | 0.5659   | 0.5410 |
| 1.0498        | 5.0   | 485  | 1.3569          | 0.5780   | 0.5600 |
| 0.9017        | 6.0   | 582  | 1.3051          | 0.6023   | 0.5909 |
| 0.8082        | 7.0   | 679  | 1.2839          | 0.6053   | 0.5973 |
| 0.7148        | 8.0   | 776  | 1.2836          | 0.5955   | 0.5890 |
| 0.6598        | 9.0   | 873  | 1.2702          | 0.6045   | 0.5961 |
| 0.6222        | 10.0  | 970  | 1.2697          | 0.6030   | 0.5963 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3