--- 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: [] --- [Visualize in Weights & Biases](https://wandb.ai/hallo23/huggingface/runs/5pgjd6az) # xls-r-amharic 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 an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.1237 - Accuracy: 0.9778 ## 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