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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
base_model: bert-base-uncased
model-index:
  - name: bert-base-uncased-cv-position-classifier
    results: []

bert-base-uncased-cv-position-classifier

This model is a fine-tuned version of 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