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emotion-classification-model

Text Classification
Transformers
Safetensors
distilbert
emotion-classification
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emotion-classification-model / README.md
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metadata
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: emotion-classification-model
    results: []

emotion-classification-model

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

  • Loss: 0.1953
  • Accuracy: 0.9225

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: 6e-05
  • train_batch_size: 16
  • eval_batch_size: 32
  • total_train_batch_size: 32
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 2
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.2344 1.0 500 0.2365 0.915
0.1408 2.0 1000 0.1953 0.9225

Framework versions

  • Transformers 4.46.2
  • Pytorch 2.5.1+cu118
  • Datasets 3.1.0
  • Tokenizers 0.20.3