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wavlm-finetuned-IEMOCAP – AI Model by VasilisAsim | AlphaNeural AI
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VasilisAsim
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wavlm-finetuned-IEMOCAP
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transformers
safetensors
wavlm
audio-classification
generated_from_trainer
microsoft/wavlm-base-plus
finetune
endpoints_compatible
us
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wavlm-finetuned-IEMOCAP
This model is a fine-tuned version of
microsoft/wavlm-base-plus
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.4042
Accuracy: 0.4972
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: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 0.1
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
6.8687
1.0
402
1.7019
0.3292
6.5214
2.0
804
1.6125
0.3671
5.9374
3.0
1206
1.5022
0.4493
5.4183
4.0
1608
1.4527
0.4798
5.2812
5.0
2010
1.4042
0.4972
Framework versions
Transformers 5.12.0
Pytorch 2.11.0+cu128
Datasets 5.0.0
Tokenizers 0.22.2
