wav2vec2-large-960h

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

wav2vec2-large-960h

This model is a fine-tuned version of facebook/wav2vec2-large-960h on an acc_dataset_v2" dataset (commit: a41c520).

It achieves the following results on the evaluation set:

• Loss: 0.6286

• Wer: 0.1538

Model description

This is a voice-2-text transcription model specialized for the acc dataset.

Training and evaluation data

Training was based on the training set in acc_dataset_v2 and evaluation based on the validation and test sets in the same dataset.

Training procedure

See the Jupyter notebook Finetuning-notebook-wav2vec2-large-960h-on-acc-data for the full training procedure.

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0001
• train_batch_size: 64
• eval_batch_size: 8
• seed: 42
• optimizer: Use 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: 15
• num_epochs: 128
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.48.2
• Pytorch 2.6.0+cu124
• Datasets 3.2.0
• Tokenizers 0.21.0