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