w2v-bert-2.0-basaa-colab-cv23.0

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

• eval_loss: 0.0974
• eval_wer: 0.1065
• eval_runtime: 43.8683
• eval_samples_per_second: 35.333
• eval_steps_per_second: 4.422
• epoch: 6.8780
• step: 2400

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_FUSED 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

Framework versions

• Transformers 4.56.2
• Pytorch 2.8.0+cu126
• Datasets 4.1.1
• Tokenizers 0.22.0