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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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["yahoo_answers_topics"], "metrics": ["accuracy"], "base_model": "bert-base-uncased", "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"}]}]}]}
transformers safetensors bert text-classification generated_from_trainer dataset:yahoo_answers_topics base_model:bert-base-uncased license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us