End of training

README.md

@@ -0,0 +1,77 @@
+---
+base_model: openai/whisper-tiny
+tags:
+- generated_from_trainer
+datasets:
+- PolyAI/minds14
+metrics:
+- wer
+model-index:
+- name: whisper-tiny-polyai-enUS_fewer_epochs
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: PolyAI/minds14
+      type: PolyAI/minds14
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.34946871310507677
+---
+
+<!-- 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. -->
+
+# whisper-tiny-polyai-enUS_fewer_epochs
+
+This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6145
+- Wer Ortho: 0.3800
+- Wer: 0.3495
+
+## 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-06
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- 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: 200
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
+| 2.9576        | 3.33  | 50   | 1.9424          | 0.5077    | 0.4050 |
+| 0.5132        | 6.67  | 100  | 0.6382          | 0.4152    | 0.3684 |
+| 0.2569        | 10.0  | 150  | 0.5925          | 0.3893    | 0.3554 |
+| 0.0973        | 13.33 | 200  | 0.6145          | 0.3800    | 0.3495 |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.1.1+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.0

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+}

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