w2v-bert-2.0-turkish-colab-CV6.1

This model is a fine-tuned version of ylacombe/w2v-bert-2.0 on the common_voice_6_1 dataset. It achieves the following results on the evaluation set:

• Loss: 0.1978
• Wer: 0.1838

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
4.4016	0.92	100	2.4338	1.0428
0.5644	1.83	200	0.2224	0.1936
0.1692	2.75	300	0.1978	0.1838

Framework versions

• Transformers 4.37.0.dev0
• Pytorch 2.1.0+cu121
• Datasets 2.16.1
• Tokenizers 0.15.0