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# distillbert-distilled-ag-news-2

This model is a fine-tuned version of [google/bert_uncased_L-8_H-256_A-4](https://huggingface.co/google/bert_uncased_L-8_H-256_A-4) on the ag_news dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1945
- Accuracy: 0.9408

## 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: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.238         | 1.0   | 3000  | 0.2240          | 0.9237   |
| 0.1873        | 2.0   | 6000  | 0.2009          | 0.9329   |
| 0.1597        | 3.0   | 9000  | 0.1919          | 0.9377   |
| 0.1495        | 4.0   | 12000 | 0.1948          | 0.9400   |
| 0.1303        | 5.0   | 15000 | 0.1945          | 0.9408   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["ag_news"], "metrics": ["accuracy"], "base_model": "google/bert_uncased_L-8_H-256_A-4", "model-index": [{"name": "distillbert-distilled-ag-news-2", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "ag_news", "type": "ag_news", "config": "default", "split": "train", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9407916666666667, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors bert text-classification generated_from_trainer dataset:ag_news base_model:google/bert_uncased_L-8_H-256_A-4 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us