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NHS-distilbert-multi
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metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: NHS-distilbert-multi
    results: []

NHS-distilbert-multi

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8248
  • Accuracy: 0.7142
  • Precision: 0.7211
  • Recall: 0.7142
  • F1: 0.7170

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: 3e-05
  • 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: linear
  • num_epochs: 6

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
0.7144 1.0 397 0.7555 0.7016 0.7157 0.7016 0.7061
0.1303 2.0 794 0.7807 0.6978 0.6991 0.6978 0.6903
2.3614 3.0 1191 0.8248 0.7142 0.7211 0.7142 0.7170

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2