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# bert-base-cased-sst2

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the sst2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2103
- Accuracy: 0.9140

## 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: 3e-05
- train_batch_size: 128
- eval_batch_size: 128
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2267        | 1.0   | 527  | 0.2103          | 0.9140   |
| 0.1091        | 2.0   | 1054 | 0.2637          | 0.9174   |
| 0.0722        | 3.0   | 1581 | 0.2673          | 0.9174   |
| 0.0467        | 4.0   | 2108 | 0.2947          | 0.9266   |
| 0.0298        | 5.0   | 2635 | 0.3344          | 0.9209   |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["sst2"], "metrics": ["accuracy"], "base_model": "bert-base-cased", "model-index": [{"name": "bert-base-cased-sst2", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "sst2", "type": "sst2", "config": "default", "split": "validation", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9139908256880734, "name": "Accuracy"}]}]}]}
transformers pytorch bert text-classification generated_from_trainer dataset:sst2 base_model:bert-base-cased license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us