w2v-bert-2.0-armenian-speech-model-CV16

This model is a fine-tuned version of facebook/w2v-bert-2.0 on the common_voice_16_0 dataset. It achieves the following results on the evaluation set:

• Loss: 0.1620
• Wer: 0.1351
• Cer: 0.0234

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: 5e-05
• train_batch_size: 16
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• 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: 500
• num_epochs: 10
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
1.3609	1.5973	300	0.1979	0.2548	0.0429
0.1429	3.192	600	0.1795	0.1918	0.0336
0.0862	4.7893	900	0.1608	0.1696	0.0293
0.0479	6.384	1200	0.1459	0.1450	0.0251
0.0243	7.9813	1500	0.1534	0.1387	0.0239
0.0105	9.576	1800	0.1620	0.1351	0.0234

Framework versions

• Transformers 4.52.4
• Pytorch 2.6.0+cu124
• Datasets 3.6.0
• Tokenizers 0.21.1