transformers safetensors bert text-classification generated_from_trainer dataset:yahoo_answers_topics base_model:google-bert/bert-base-uncased base_model:finetune:google-bert/bert-base-uncased license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: bert-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: 0.6518
      name: Accuracy
---

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# topic_classification

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the yahoo_answers_topics dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1769
- Accuracy: 0.6518

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.005         | 1.0   | 625  | 1.0478          | 0.6519   |
| 0.7717        | 2.0   | 1250 | 1.0482          | 0.6557   |
| 0.4566        | 3.0   | 1875 | 1.1769          | 0.6518   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
