pytorch bert text-classification transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
model-index:
- name: bert-base-uncased-cv-position-classifier
  results: []
---

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# bert-base-uncased-cv-position-classifier

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: 1.6924
- Accuracy: {'accuracy': 0.5780703216130645}
- F1: {'f1': 0.5780703216130645}
- Precision: {'precision': 0.5780703216130645}

## 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: 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy                         | F1                         | Precision                         |
|:-------------:|:-----:|:----:|:---------------:|:--------------------------------:|:--------------------------:|:---------------------------------:|
| 2.0336        | 1.14  | 1000 | 1.8856          | {'accuracy': 0.5259123479420097} | {'f1': 0.5259123479420097} | {'precision': 0.5259123479420097} |
| 1.5348        | 2.28  | 2000 | 1.6924          | {'accuracy': 0.5780703216130645} | {'f1': 0.5780703216130645} | {'precision': 0.5780703216130645} |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.8.1+cu111
- Datasets 1.6.2
- Tokenizers 0.12.1
