Wav2vec2 Base 10lang Ssl

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0003
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 64
• 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: 500
• num_epochs: 4

Training results

Framework versions

• Transformers 5.1.0
• Pytorch 2.7.1+cu118
• Datasets 2.21.0
• Tokenizers 0.22.2

model.safetensors

safetensors · 363 MB · SHA-256 a589334a9a84…14dd · Hugging Face

--- library_name: transformers license: apache-2.0 base_model: facebook/wav2vec2-base tags: - generated_from_trainer model-index: - name: wav2vec2-base-10lang-ssl results: [] datasets: - 27Group/shared_task language: - ar - de - en - es - id - ja - pt - ru - ur - vi metrics: - wer - f1 pipeline_tag: audio-classification --- <!-- 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-base-10lang-ssl This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. ## 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: 0.0003 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 64 - 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: 500 - num_epochs: 4 ### Training results ### Framework versions - Transformers 5.1.0 - Pytorch 2.7.1+cu118 - Datasets 2.21.0 - Tokenizers 0.22.2