End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: openai/whisper-tiny
+tags:
+- generated_from_trainer
+datasets:
+- PolyAI/minds14
+metrics:
+- wer
+model-index:
+- name: whisper-tiny-en
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: PolyAI/minds14
+      type: PolyAI/minds14
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.2622739018087855
+---
+
+<!-- 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-en
+
+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: 0.6208
+- Wer Ortho: 0.2773
+- Wer: 0.2623
+
+## 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: 1
+- eval_batch_size: 1
+- seed: 42
+- gradient_accumulation_steps: 16
+- total_train_batch_size: 16
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: constant_with_warmup
+- lr_scheduler_warmup_steps: 5
+- training_steps: 500
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Wer Ortho | Wer    |
+|:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|
+| 0.1079        | 17.8629 | 500  | 0.6208          | 0.2773    | 0.2623 |
+
+
+### Framework versions
+
+- Transformers 4.57.1
+- Pytorch 2.9.0
+- Datasets 2.18.0
+- Tokenizers 0.22.1