wav2vec2-large-xlsr-sw-ASR

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the Swahili dataset from common voice. It achieves the following results on the evaluation set:

• Loss: 0.1446
• Wer: 0.2453

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 1000
• num_epochs: 1
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
No log	0.0740	1000	0.8588	0.7661
No log	0.1480	2000	0.3139	0.4159
1.9537	0.2220	3000	0.2514	0.3524
1.9537	0.2960	4000	0.2217	0.3292
1.9537	0.3700	5000	0.1986	0.3029
0.3639	0.4440	6000	0.1847	0.2903
0.3639	0.5181	7000	0.1754	0.2747
0.3639	0.5921	8000	0.1657	0.2689
0.3039	0.6661	9000	0.1587	0.2598
0.3039	0.7401	10000	0.1565	0.2560
0.3039	0.8141	11000	0.1529	0.2518
0.2688	0.8881	12000	0.1478	0.2476
0.2688	0.9621	13000	0.1446	0.2453

Framework versions

• Transformers 4.53.0
• Pytorch 2.6.0+cu124
• Datasets 2.14.4
• Tokenizers 0.21.2