Wav2vec2 Base 100k Voxpopuli Finetuned Minds

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0001
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• 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
• num_epochs: 10

Training results

Framework versions

• Transformers 4.57.3
• Pytorch 2.9.0+cu126
• Datasets 3.6.0
• Tokenizers 0.22.1

--- library_name: transformers license: cc-by-nc-4.0 base_model: facebook/wav2vec2-base-100k-voxpopuli tags: - generated_from_trainer metrics: - accuracy model-index: - name: wav2vec2-base-100k-voxpopuli-finetuned-minds results: [] --- <!-- 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-100k-voxpopuli-finetuned-minds This model is a fine-tuned version of [facebook/wav2vec2-base-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-base-100k-voxpopuli) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 2.6483 - Accuracy: 0.0796 ## 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: 0.0001 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - 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 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 2.6425 | 1.0 | 57 | 2.6429 | 0.0442 | | 2.6422 | 2.0 | 114 | 2.6458 | 0.0354 | | 2.6434 | 3.0 | 171 | 2.6437 | 0.0531 | | 2.6452 | 4.0 | 228 | 2.6485 | 0.0531 | | 2.6256 | 5.0 | 285 | 2.6475 | 0.0531 | | 2.6384 | 6.0 | 342 | 2.6489 | 0.0531 | | 2.6259 | 7.0 | 399 | 2.6496 | 0.0354 | | 2.645 | 8.0 | 456 | 2.6484 | 0.0531 | | 2.6144 | 9.0 | 513 | 2.6482 | 0.0796 | | 2.6338 | 10.0 | 570 | 2.6483 | 0.0796 | ### Framework versions - Transformers 4.57.3 - Pytorch 2.9.0+cu126 - Datasets 3.6.0 - Tokenizers 0.22.1