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human-emotion-detection – AI Model by Hemg | AlphaNeural AI
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Hemg
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human-emotion-detection
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transformers
tensorboard
safetensors
wav2vec2
audio-classification
generated_from_trainer
jonatasgrosman/wav2vec2-large-xlsr-53-english
finetune
apache-2.0
endpoints_compatible
us
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human-emotion-detection
This model is a fine-tuned version of
jonatasgrosman/wav2vec2-large-xlsr-53-english
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.9555
Accuracy: 0.6262
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: 0.0005
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.01
num_epochs: 4
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
1.5875
1.0
40
1.2574
0.5133
1.1637
2.0
80
1.0852
0.5590
0.9827
3.0
120
1.0048
0.6090
0.8683
4.0
160
0.9555
0.6262
Framework versions
Transformers 4.39.3
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2
