w2v-bert-2.0-bas-cv24

This model is a fine-tuned version of facebook/w2v-bert-2.0 on the None dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.8710
• eval_wer: 0.4587
• eval_cer: 0.1451
• eval_runtime: 42.1734
• eval_samples_per_second: 36.753
• eval_steps_per_second: 9.2
• epoch: 1.8558
• step: 200

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: 8
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 4
• 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_ratio: 0.1
• num_epochs: 15
• mixed_precision_training: Native AMP

Framework versions

• Transformers 4.57.3
• Pytorch 2.4.1+cu124
• Datasets 4.4.1
• Tokenizers 0.22.1