--- language: - es license: apache-2.0 base_model: openai/whisper-medium tags: - generated_from_trainer datasets: - Mezosky/es_clinical_assistance_10k metrics: - wer model-index: - name: Whisper Chilean Spanish Medium results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Mezosky/es_clinical_assistance_10k type: Mezosky/es_clinical_assistance_10k metrics: - name: Wer type: wer value: 7.774513918030494 --- # Whisper Chilean Spanish Medium This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Mezosky/es_clinical_assistance_10k dataset. It achieves the following results on the evaluation set: - Loss: 0.1058 - Wer: 7.7745 ## 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: 16 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 1000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.6275 | 0.17 | 100 | 0.5455 | 13.3333 | | 0.185 | 0.34 | 200 | 0.1782 | 10.7316 | | 0.1523 | 0.51 | 300 | 0.1539 | 10.9106 | | 0.1373 | 0.69 | 400 | 0.1399 | 10.1329 | | 0.1538 | 0.86 | 500 | 0.1322 | 17.5493 | | 0.1007 | 1.03 | 600 | 0.1238 | 8.4963 | | 0.0782 | 1.2 | 700 | 0.1187 | 8.4599 | | 0.0722 | 1.37 | 800 | 0.1128 | 7.8137 | | 0.0715 | 1.54 | 900 | 0.1081 | 7.6934 | | 0.0927 | 1.72 | 1000 | 0.1058 | 7.7745 | ### Framework versions - Transformers 4.39.3 - Pytorch 2.2.2+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2