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# model

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the rotten_tomatoes dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7383
- Accuracy: 0.8574

## 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: 64
- eval_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 134  | 0.3619          | 0.8527   |
| No log        | 2.0   | 268  | 0.4070          | 0.8612   |
| No log        | 3.0   | 402  | 0.5239          | 0.8480   |
| 0.183         | 4.0   | 536  | 0.6758          | 0.8499   |
| 0.183         | 5.0   | 670  | 0.7383          | 0.8574   |


### 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": ["rotten_tomatoes"], "metrics": ["accuracy"], "base_model": "bert-base-uncased", "model-index": [{"name": "model", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "rotten_tomatoes", "type": "rotten_tomatoes", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8574108818011257, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors bert text-classification generated_from_trainer dataset:rotten_tomatoes base_model:bert-base-uncased license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us