--- license: apache-2.0 tags: - generated_from_trainer datasets: - timit_asr model-index: - name: wav2vec2-base_phoneme-timit_english_timit-4k_001 results: [] language: - en metrics: - wer library_name: transformers pipeline_tag: automatic-speech-recognition --- # wav2vec2-base_phoneme-timit_english_timit-4k_001 This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the timit dataset. It achieves the following results on the evaluation set: - Loss: 0.6361 - Per: 0.1195 ## 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: 16 - 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: 5000 - training_steps: 10000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Per | |:-------------:|:-----:|:-----:|:---------------:|:------:| | 5.2193 | 3.46 | 1000 | 3.5945 | 0.9617 | | 1.5174 | 6.92 | 2000 | 0.5574 | 0.1665 | | 0.5246 | 10.38 | 3000 | 0.4228 | 0.1503 | | 0.3915 | 13.84 | 4000 | 0.4276 | 0.1512 | | 0.3293 | 17.3 | 5000 | 0.4656 | 0.1517 | | 0.2757 | 20.76 | 6000 | 0.4719 | 0.1486 | | 0.209 | 24.22 | 7000 | 0.5314 | 0.1478 | | 0.1589 | 27.68 | 8000 | 0.6102 | 0.1484 | | 0.1207 | 31.14 | 9000 | 0.6449 | 0.1484 | | 0.0951 | 34.6 | 10000 | 0.6579 | 0.1471 | ### Framework versions - Transformers 4.28.1 - Pytorch 2.0.1 - Datasets 2.18.0 - Tokenizers 0.13.3