transformers safetensors distilbert text-classification generated_from_trainer dataset:yahoo_answers_topics base_model:distilbert/distilbert-base-uncased base_model:finetune:distilbert/distilbert-base-uncased license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: distilbert-base-uncased
datasets:
- yahoo_answers_topics
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: topic_classification
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: yahoo_answers_topics
      type: yahoo_answers_topics
      config: yahoo_answers_topics
      split: test
      args: yahoo_answers_topics
    metrics:
    - type: accuracy
      value: 0.7125166666666667
      name: Accuracy
---

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# topic_classification

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the yahoo_answers_topics dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9119
- Accuracy: 0.7125

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 30000

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 1.0187        | 0.0286 | 5000  | 1.0647          | 0.6695   |
| 0.9944        | 0.0571 | 10000 | 1.0281          | 0.6782   |
| 0.9641        | 0.0857 | 15000 | 0.9694          | 0.6969   |
| 0.8833        | 0.1143 | 20000 | 0.9426          | 0.7045   |
| 0.9416        | 0.1429 | 25000 | 0.9239          | 0.7093   |
| 0.932         | 0.1714 | 30000 | 0.9119          | 0.7125   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
