metadata

library_name: transformers
license: apache-2.0
base_model: m3hrdadfi/hubert-base-persian-speech-emotion-recognition
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: Hubert-fine-tuned-persian
    results: []

Hubert-fine-tuned-persian

This model is a fine-tuned version of m3hrdadfi/hubert-base-persian-speech-emotion-recognition on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.7102
Accuracy: 0.7585
Precision: 0.7838
Recall: 0.6493
F1: 0.7102
Precision Neutral: 0.7432
Recall Neutral: 0.85
F1 Neutral: 0.7930
Precision Anger: 0.7838
Recall Anger: 0.6493
F1 Anger: 0.7102

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: 4
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 500
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Precision Neutral	Recall Neutral	F1 Neutral	Precision Anger	Recall Anger	F1 Anger
0.6917	1.0	294	0.6704	0.5578	0.5078	0.9701	0.6667	0.8947	0.2125	0.3434	0.5078	0.9701	0.6667
0.6453	2.0	588	0.6077	0.7007	0.8194	0.4403	0.5728	0.6622	0.9187	0.7696	0.8194	0.4403	0.5728
0.5272	3.0	882	0.7842	0.6633	0.9487	0.2761	0.4277	0.6196	0.9875	0.7614	0.9487	0.2761	0.4277
0.4118	4.0	1176	0.6566	0.7449	0.736	0.6866	0.7104	0.7515	0.7937	0.7720	0.736	0.6866	0.7104
0.4956	5.0	1470	0.7102	0.7585	0.7838	0.6493	0.7102	0.7432	0.85	0.7930	0.7838	0.6493	0.7102

Framework versions

Transformers 4.47.1
Pytorch 2.5.1+cu124
Datasets 2.18.0
Tokenizers 0.21.0