emotion-classification

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emotion-classification

This model was trained from scratch on the imagefolder dataset. It achieves the following results on the evaluation set:

• Loss: 0.8208
• Accuracy: 0.875

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: 3e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 128
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 3

Training results

KeyboardInterrupt: because full disk, continue from checkpoint 270 / from epoch 54 checkpoint = "C:\Users\willi\Documents\MachineLearning_Collab\model\emotion-classification\checkpoint-270"

The result of evaluation from trainer.evaluate(eval_dataset=emotion["test"]):

{'eval_loss': 0.8208037614822388, 'eval_accuracy': 0.875, 'eval_runtime': 5.3137, 'eval_samples_per_second': 30.111, 'eval_steps_per_second': 0.941, 'epoch': 3.0}

Framework versions

• Transformers 4.41.2
• Pytorch 2.4.0
• Datasets 2.21.0
• Tokenizers 0.19.1