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Librarian Bot: Add base_model information to model (#2)
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - massive
metrics:
  - accuracy
base_model: distilbert-base-uncased
model-index:
  - name: distilbert-base-uncased-finetuned-massive-intent-detection-english
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: massive
          type: massive
          args: en-US
        metrics:
          - type: accuracy
            value: 0.886684599865501
            name: Accuracy

distilbert-base-uncased-finetuned-massive-intent-detection-english

This model is a fine-tuned version of distilbert-base-uncased on the massive dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4873
  • Accuracy: 0.8867

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: 32
  • eval_batch_size: 32
  • 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 Accuracy
2.5849 1.0 360 1.3826 0.7359
1.0662 2.0 720 0.7454 0.8357
0.5947 3.0 1080 0.5668 0.8642
0.3824 4.0 1440 0.5007 0.8770
0.2649 5.0 1800 0.4829 0.8824
0.1877 6.0 2160 0.4843 0.8824
0.1377 7.0 2520 0.4858 0.8834
0.1067 8.0 2880 0.4924 0.8864

Framework versions

  • Transformers 4.19.2
  • Pytorch 1.11.0+cu113
  • Datasets 2.2.2
  • Tokenizers 0.12.1