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# bert-base-uncased-dietdupe-foodb-desc

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6188

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 124  | 1.6109          |
| No log        | 2.0   | 248  | 1.6449          |
| No log        | 3.0   | 372  | 1.7693          |
| No log        | 4.0   | 496  | 1.7404          |
| 1.8504        | 5.0   | 620  | 1.6661          |
| 1.8504        | 6.0   | 744  | 1.5235          |
| 1.8504        | 7.0   | 868  | 1.5884          |
| 1.8504        | 8.0   | 992  | 1.6669          |
| 1.6616        | 9.0   | 1116 | 1.4289          |
| 1.6616        | 10.0  | 1240 | 1.6314          |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "bert-base-uncased", "model-index": [{"name": "bert-base-uncased-dietdupe-foodb-desc", "results": []}]}
transformers tensorboard safetensors bert fill-mask generated_from_trainer base_model:bert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us