End of training

README.md

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+---
+license: mit
+base_model: distil-whisper/distil-medium.en
+tags:
+- generated_from_trainer
+datasets:
+- dysarthria
+metrics:
+- accuracy
+model-index:
+- name: distil-medium.en-dysarthia-non-dysathira-detection-fm
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: Dysarthria
+      type: dysarthria
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.975
+---
+
+<!-- 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. -->
+
+# distil-medium.en-dysarthia-non-dysathira-detection-fm
+
+This model is a fine-tuned version of [distil-whisper/distil-medium.en](https://huggingface.co/distil-whisper/distil-medium.en) on the Dysarthria dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1593
+- Accuracy: 0.975
+
+## 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: 5e-05
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.875         | 1.0   | 160  | 0.4243          | 0.8875   |
+| 0.0264        | 2.0   | 320  | 1.2160          | 0.8125   |
+| 0.0115        | 3.0   | 480  | 0.2111          | 0.95     |
+| 0.3632        | 4.0   | 640  | 0.1856          | 0.975    |
+| 0.0933        | 5.0   | 800  | 0.7655          | 0.9      |
+| 0.0003        | 6.0   | 960  | 0.6221          | 0.9      |
+| 0.0001        | 7.0   | 1120 | 0.1163          | 0.9875   |
+| 0.0001        | 8.0   | 1280 | 0.3188          | 0.95     |
+| 0.0001        | 9.0   | 1440 | 0.1662          | 0.975    |
+| 0.0001        | 10.0  | 1600 | 0.1593          | 0.975    |
+
+
+### Framework versions
+
+- Transformers 4.41.0.dev0
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

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