| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition |
| tags: |
| - generated_from_trainer |
| datasets: |
| - audiofolder |
| metrics: |
| - accuracy |
| - f1 |
| - precision |
| - recall |
| model-index: |
| - name: wav2vec2-lg-xlsr-en-speech-emotion-recognition-finetuned-babycry-v2 |
| results: |
| - task: |
| name: Audio Classification |
| type: audio-classification |
| dataset: |
| name: audiofolder |
| type: audiofolder |
| config: default |
| split: train |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: |
| accuracy: 0.8043478260869565 |
| - name: F1 |
| type: f1 |
| value: 0.7171293871136721 |
| - name: Precision |
| type: precision |
| value: 0.6469754253308129 |
| - name: Recall |
| type: recall |
| value: 0.8043478260869565 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # wav2vec2-lg-xlsr-en-speech-emotion-recognition-finetuned-babycry-v2 |
|
|
| This model is a fine-tuned version of [ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition](https://huggingface.co/ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition) on the audiofolder dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.8522 |
| - Accuracy: {'accuracy': 0.8043478260869565} |
| - F1: 0.7171 |
| - Precision: 0.6470 |
| - Recall: 0.8043 |
|
|
| ## 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: 0.0001 |
| - train_batch_size: 4 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 8 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 3 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
| |:-------------:|:------:|:----:|:---------------:|:--------------------------------:|:------:|:---------:|:------:| |
| | 0.6078 | 0.4854 | 25 | 0.8682 | {'accuracy': 0.8043478260869565} | 0.7171 | 0.6470 | 0.8043 | |
| | 0.7269 | 0.9709 | 50 | 0.8559 | {'accuracy': 0.8043478260869565} | 0.7171 | 0.6470 | 0.8043 | |
| | 0.6815 | 1.4563 | 75 | 0.8204 | {'accuracy': 0.8043478260869565} | 0.7171 | 0.6470 | 0.8043 | |
| | 0.6144 | 1.9417 | 100 | 0.8417 | {'accuracy': 0.8043478260869565} | 0.7171 | 0.6470 | 0.8043 | |
| | 0.6246 | 2.4272 | 125 | 0.8454 | {'accuracy': 0.8043478260869565} | 0.7171 | 0.6470 | 0.8043 | |
| | 0.5687 | 2.9126 | 150 | 0.8527 | {'accuracy': 0.8043478260869565} | 0.7171 | 0.6470 | 0.8043 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.44.2 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.0.1 |
| - Tokenizers 0.19.1 |
|
|
