--- license: apache-2.0 base_model: facebook/wav2vec2-base tags: - generated_from_trainer datasets: - minds14 metrics: - wer model-index: - name: my_awesome_asr_mind_model results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: minds14 type: minds14 config: en-US split: None args: en-US metrics: - name: Wer type: wer value: 1.0 --- # my_awesome_asr_mind_model This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the minds14 dataset. It achieves the following results on the evaluation set: - Loss: 4.4234 - Wer: 1.0 ## 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: 1e-05 - train_batch_size: 4 - eval_batch_size: 5 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 8 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | 41.4282 | 1.0 | 19 | 30.2334 | 1.1822 | | 28.1402 | 2.0 | 38 | 13.5933 | 1.0 | | 11.5171 | 3.0 | 57 | 6.6439 | 1.0 | | 6.9951 | 4.0 | 76 | 4.8219 | 1.0 | | 5.3819 | 5.0 | 95 | 4.4234 | 1.0 | ### Framework versions - Transformers 4.41.0 - Pytorch 2.3.0+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1