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metadata
license: mit
tags:
  - generated_from_trainer
datasets:
  - sst2
metrics:
  - accuracy
base_model: prajjwal1/bert-tiny
model-index:
  - name: sentiment-model-saagie
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: sst2
          type: sst2
          args: default
        metrics:
          - type: accuracy
            value: 0.7766666666666666
            name: Accuracy

sentiment-model-saagie

This model is a fine-tuned version of prajjwal1/bert-tiny on the sst2 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5524
  • Accuracy: 0.7767

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
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.5173 1.0 1500 0.4780 0.775
0.3824 2.0 3000 0.5339 0.7767
0.3359 3.0 4500 0.5524 0.7767

Framework versions

  • Transformers 4.18.0
  • Pytorch 1.8.1
  • Datasets 2.12.0
  • Tokenizers 0.12.1