--- language: - dv license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - mozilla-foundation/common_voice_13_0 metrics: - wer model-index: - name: dysarthria_emo_enhancer_0_0 results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: custom_torgo_0_0 type: mozilla-foundation/common_voice_13_0 metrics: - name: Wer type: wer value: 33.51724137931035 --- # dysarthria_emo_enhancer_0_0 This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the custom_torgo_0_0 dataset. It achieves the following results on the evaluation set: - Loss: 0.5371 - Wer Ortho: 50.5634 - Wer: 33.5172 And the following results on the TORGO + UAS training set: - Acc: 0.30 - Wer: 80.63 ## 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: 8 - eval_batch_size: 16 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: constant_with_warmup - lr_scheduler_warmup_steps: 50 - training_steps: 500 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:| | 3.4478 | 0.35 | 50 | 3.6845 | 67.3239 | 50.4828 | | 2.3364 | 0.7 | 100 | 2.4193 | 60.5634 | 44.0 | | 0.2024 | 1.05 | 150 | 0.7172 | 56.4789 | 36.6897 | | 0.3609 | 1.39 | 200 | 0.5792 | 54.9296 | 36.8276 | | 0.2227 | 1.74 | 250 | 0.5763 | 53.9437 | 35.4483 | | 0.0752 | 2.09 | 300 | 0.5516 | 53.6620 | 34.8966 | | 0.0249 | 2.44 | 350 | 0.5511 | 46.7606 | 29.5172 | | 0.17 | 2.79 | 400 | 0.5289 | 50.4225 | 31.8621 | | 0.0736 | 3.14 | 450 | 0.5618 | 51.5493 | 32.5517 | | 0.0375 | 3.48 | 500 | 0.5371 | 50.5634 | 33.5172 | ### Framework versions - Transformers 4.34.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.5 - Tokenizers 0.14.1