metadata
license: apache-2.0
base_model: ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: xls-r-amharic
results: []
xls-r-amharic
This model is a fine-tuned version of ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0901
- Accuracy: 0.9818
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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- 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
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2847 | 2.0202 | 500 | 0.2479 | 0.9212 |
| 0.1138 | 4.0404 | 1000 | 0.2063 | 0.9434 |
| 0.0614 | 6.0606 | 1500 | 0.1415 | 0.9657 |
| 0.0349 | 8.0808 | 2000 | 0.1383 | 0.9737 |
| 0.0143 | 10.1010 | 2500 | 0.0901 | 0.9818 |
| 0.0178 | 12.1212 | 3000 | 0.1188 | 0.9778 |
| 0.0222 | 14.1414 | 3500 | 0.1237 | 0.9778 |
Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.1.2
- Datasets 2.19.1.dev0
- Tokenizers 0.19.1