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# LLM

This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7030
- Accuracy: 0.15

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- 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   | 12   | 1.6756          | 0.1      |
| No log        | 2.0   | 24   | 1.6728          | 0.15     |
| No log        | 3.0   | 36   | 1.6773          | 0.2      |
| No log        | 4.0   | 48   | 1.6952          | 0.2      |
| No log        | 5.0   | 60   | 1.7030          | 0.15     |


### Framework versions

- Transformers 4.32.1
- Pytorch 1.13.1
- Datasets 2.14.4
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "bert-large-uncased", "model-index": [{"name": "LLM", "results": []}]}
transformers pytorch bert multiple-choice generated_from_trainer base_model:bert-large-uncased license:apache-2.0 endpoints_compatible region:us