--- license: apache-2.0 base_model: facebook/wav2vec2-base-960h tags: - generated_from_trainer metrics: - wer model-index: - name: wav2vec2-960h-fine-tuning-2 results: [] --- [Visualize in Weights & Biases](https://wandb.ai/ashe194-700/facebook-wav-2-vec-fine-tuning/runs/aso83mbs) # wav2vec2-960h-fine-tuning-2 This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.9325 - Wer: 11.2741 ## 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: 4e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 64 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 4 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:-------:| | No log | 0.9935 | 76 | 1.3301 | 15.9156 | | No log | 2.0 | 153 | 3.8761 | 17.1732 | | No log | 2.9935 | 229 | 1.8980 | 13.3403 | | No log | 3.9739 | 304 | 0.9325 | 11.2741 | ### Framework versions - Transformers 4.42.3 - Pytorch 2.3.1+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1