emotion_classifier / README.md
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emotion-classifier
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metadata
library_name: transformers
license: mit
base_model: abdeljalilELmajjodi/model
tags:
  - generated_from_trainer
metrics:
  - f1
model-index:
  - name: emotion_classifier
    results: []

emotion_classifier

This model is a fine-tuned version of abdeljalilELmajjodi/model on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.7268
  • F1: {'f1': 0.4749679405113014}

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: 4
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • 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
  • lr_scheduler_warmup_ratio: 0.03
  • num_epochs: 5
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss F1
6.8728 0.9950 100 1.8998 {'f1': 0.3554471709728371}
6.545 1.9851 200 1.7557 {'f1': 0.4311025882104702}
5.7745 2.9751 300 1.7189 {'f1': 0.45241170661760866}
5.1439 3.9652 400 1.7268 {'f1': 0.4629496833729773}
4.6931 4.9552 500 1.7268 {'f1': 0.4749679405113014}

Framework versions

  • Transformers 4.47.1
  • Pytorch 2.5.1+cu121
  • Datasets 3.2.0
  • Tokenizers 0.21.0