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Model: mahendra0203/whisper-medium-medical
Source: Original Platform

README.md

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+---
+license: apache-2.0
+base_model: openai/whisper-medium
+tags:
+- generated_from_trainer
+datasets:
+- yashtiwari/PaulMooney-Medical-ASR-Data
+metrics:
+- wer
+model-index:
+- name: Whisper Medium Medical
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Medical ASR
+      type: yashtiwari/PaulMooney-Medical-ASR-Data
+    metrics:
+    - name: Wer
+      type: wer
+      value: 16.051170649287954
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/jutsu-labs/huggingface/runs/nnp3wvhl)
+# Whisper Medium Medical
+
+This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Medical ASR dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0567
+- Wer: 16.0512
+
+## 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: 32
+- 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: 50
+- training_steps: 500
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Wer     |
+|:-------------:|:------:|:----:|:---------------:|:-------:|
+| 0.4817        | 0.5405 | 100  | 0.1982          | 12.8651 |
+| 0.104         | 1.0811 | 200  | 0.0839          | 10.3065 |
+| 0.0549        | 1.6216 | 300  | 0.0643          | 15.9063 |
+| 0.0245        | 2.1622 | 400  | 0.0610          | 14.0961 |
+| 0.012         | 2.7027 | 500  | 0.0567          | 16.0512 |
+
+
+### Framework versions
+
+- Transformers 4.42.4
+- Pytorch 2.2.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1