cahya/wav2vec2-base-turkish

This model is a fine-tuned version of cahya/wav2vec2-base-turkish-artificial-cv on the COMMON_VOICE - TR dataset. It achieves the following results on the evaluation set:

	Dataset	WER	CER
1	Common Voice 6.1	9.437	3.325
2	Common Voice 7.0	8.147	2.802
3	Common Voice 8.0	8.335	2.336
4	Speech Recognition Community	28.011	10.66

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

The following datasets were used for finetuning:

• Common Voice 7.0 TR 'train', 'validation' and 'other' split were used for training.
• Media Speech
• Magic Hub

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 7.5e-06
• train_batch_size: 6
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 24
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 2000
• num_epochs: 5.0

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.1224	3.45	500	0.1641	0.1396

Framework versions

• Transformers 4.17.0.dev0
• Pytorch 1.10.1+cu102
• Datasets 1.18.2
• Tokenizers 0.10.3