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Librarian Bot: Add base_model information to model
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - emotion
metrics:
  - accuracy
  - f1
base_model: distilbert-base-uncased
model-index:
  - name: distilbert-base-uncased-finetuned-emotion
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: emotion
          type: emotion
          config: default
          split: train
          args: default
        metrics:
          - type: accuracy
            value: 0.935
            name: Accuracy
          - type: f1
            value: 0.9351083637430424
            name: F1

distilbert-base-uncased-finetuned-emotion

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

  • Loss: 0.1582
  • Accuracy: 0.935
  • F1: 0.9351

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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 4

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
0.7703 1.0 250 0.2588 0.918 0.9165
0.2031 2.0 500 0.1773 0.928 0.9282
0.1385 3.0 750 0.1593 0.934 0.9342
0.1101 4.0 1000 0.1582 0.935 0.9351

Framework versions

  • Transformers 4.24.0
  • Pytorch 1.12.1+cu113
  • Datasets 2.6.1
  • Tokenizers 0.13.1