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skylord/pharma_classification
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metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
model-index:
  - name: pharma_classification
    results: []

pharma_classification

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: 0.5315
  • Accuracy: 0.9581
  • F1: 0.9506

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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • training_steps: 30000

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
0.0035 5.99 5000 0.2892 0.9539 0.9554
0.0137 11.98 10000 0.2620 0.9641 0.9600
0.0 17.96 15000 0.4022 0.9611 0.9586
0.0001 23.95 20000 0.3838 0.9611 0.9552
0.0 29.94 25000 0.4363 0.9575 0.9490
0.0 35.93 30000 0.5315 0.9581 0.9506

Framework versions

  • Transformers 4.39.0.dev0
  • Pytorch 2.2.0+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2