--- license: apache-2.0 base_model: facebook/wav2vec2-base-960h tags: - generated_from_trainer metrics: - wer model-index: - name: wav2vec2-960h-fine-tuning results: [] --- [Visualize in Weights & Biases](https://wandb.ai/ashe194-700/facebook-wav-2-vec-fine-tuning/runs/vqwjvpmo) # wav2vec2-960h-fine-tuning 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: 5.8952 - Wer: 99.9699 ## 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: 32 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 1000 - num_epochs: 3 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:-------:| | 15.6622 | 0.6536 | 100 | 56.5642 | 99.9699 | | 9.4272 | 1.3072 | 200 | 8.8586 | 99.9699 | | 4.5296 | 1.9608 | 300 | 5.3600 | 99.9699 | | 3.4224 | 2.6144 | 400 | 5.8952 | 99.9699 | ### Framework versions - Transformers 4.42.3 - Pytorch 2.3.1+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1