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ahmmedasaad2772
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wav2vec2-base-arabic_speech_emotion_recognition

Audio Classification
Transformers
PyTorch
TensorBoard
wav2vec2
Generated from Trainer
Inference Endpoints
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - audiofolder
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: wav2vec2-base-arabic_speech_emotion_recognition
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # wav2vec2-base-arabic_speech_emotion_recognition
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0430
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+ - Accuracy: 0.9992
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+ - Weighted f1: 0.9992
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+ - Micro f1: 0.9992
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+ - Macro f1: 0.9993
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+ - Weighted recall: 0.9992
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+ - Micro recall: 0.9992
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+ - Macro recall: 0.9992
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+ - Weighted precision: 0.9992
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+ - Micro precision: 0.9992
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+ - Macro precision: 0.9993
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 3e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 | Micro f1 | Macro f1 | Weighted recall | Micro recall | Macro recall | Weighted precision | Micro precision | Macro precision |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
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+ | 1.6078 | 0.98 | 29 | 1.4403 | 0.5227 | 0.4478 | 0.5227 | 0.4426 | 0.5227 | 0.5227 | 0.5187 | 0.4200 | 0.5227 | 0.4145 |
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+ | 1.6078 | 1.98 | 58 | 0.7310 | 0.9808 | 0.9808 | 0.9808 | 0.9809 | 0.9808 | 0.9808 | 0.9799 | 0.9816 | 0.9808 | 0.9827 |
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+ | 1.6078 | 2.98 | 87 | 0.2797 | 0.9992 | 0.9992 | 0.9992 | 0.9993 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9993 |
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+ | 1.6078 | 3.98 | 116 | 0.1361 | 0.9992 | 0.9992 | 0.9992 | 0.9993 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9993 |
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+ | 1.6078 | 4.98 | 145 | 0.0855 | 0.9992 | 0.9992 | 0.9992 | 0.9993 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9993 |
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+ | 1.6078 | 5.98 | 174 | 0.0638 | 0.9992 | 0.9992 | 0.9992 | 0.9993 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9993 |
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+ | 1.6078 | 6.98 | 203 | 0.0529 | 0.9992 | 0.9992 | 0.9992 | 0.9993 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9993 |
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+ | 1.6078 | 7.98 | 232 | 0.0470 | 0.9992 | 0.9992 | 0.9992 | 0.9993 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9993 |
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+ | 1.6078 | 8.98 | 261 | 0.0440 | 0.9992 | 0.9992 | 0.9992 | 0.9993 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9993 |
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+ | 1.6078 | 9.98 | 290 | 0.0430 | 0.9992 | 0.9992 | 0.9992 | 0.9993 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9993 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.26.1
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.13.3