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# bert_trainer

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.5246909856796265
- eval_accuracy: 0.8830541237113402
- eval_runtime: 70.1829
- eval_samples_per_second: 44.227
- eval_steps_per_second: 2.764
- epoch: 3.87
- step: 3000

## 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: 7.308177098205707e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 3000

### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "bert-base-cased", "model-index": [{"name": "bert_trainer", "results": []}]}
transformers tensorboard safetensors bert text-classification generated_from_trainer base_model:bert-base-cased license:apache-2.0 autotrain_compatible endpoints_compatible region:us