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results

This model is a fine-tuned version of r-f/wav2vec-english-speech-emotion-recognition on an unknown dataset. It achieves the following results on the evaluation set:

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The following hyperparameters were used during training:

learning_rate: 0.001
train_batch_size: 10
eval_batch_size: 5
seed: 42
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_steps: 50
num_epochs: 15
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.4918	1.0	232	1.3591	0.3672
1.0899	2.0	464	0.9012	0.5672
0.9523	3.0	696	1.2430	0.4862
0.8062	4.0	928	0.6423	0.7759
0.5591	5.0	1160	0.5161	0.8276
0.4538	6.0	1392	0.6369	0.8069
0.3527	7.0	1624	0.2526	0.9207
0.3833	8.0	1856	0.2226	0.9328
0.2532	9.0	2088	0.1955	0.9466
0.1296	10.0	2320	0.1860	0.9483
0.144	11.0	2552	0.1885	0.9552
0.1976	12.0	2784	0.1243	0.9655
0.0147	13.0	3016	0.1375	0.9655
0.0149	14.0	3248	0.1061	0.9776
0.0199	15.0	3480	0.1011	0.9724