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emotion-detectioN888 – AI Model by Hemg | AlphaNeural AI
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Hemg
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emotion-detectioN888
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transformers
tensorboard
safetensors
wav2vec2
audio-classification
generated_from_trainer
facebook/wav2vec2-base
finetune
apache-2.0
endpoints_compatible
us
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emotion-detectioN888
This model is a fine-tuned version of
facebook/wav2vec2-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.1607
Accuracy: 0.5375
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: 0.0003
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: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
1.566
1.0
80
1.2818
0.5039
1.2082
2.0
160
1.1607
0.5375
Framework versions
Transformers 4.39.3
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2
