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: opria123/whisper-tiny-minds14-finetuned
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: PolyAI/minds14
+      type: PolyAI/minds14
+      config: en-US
+      split: train
+      args: en-US
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.33436150524367675
+---
+
+<!-- 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. -->
+
+# opria123/whisper-tiny-minds14-finetuned
+
+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: 0.8674
+- Wer: 0.3344
+- Wer Ortho: 0.3270
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 4000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch    | Step | Validation Loss | Wer    | Wer Ortho |
+|:-------------:|:--------:|:----:|:---------------:|:------:|:---------:|
+| 0.0005        | 34.4912  | 1000 | 0.7591          | 0.3368 | 0.3245    |
+| 0.0001        | 68.9825  | 2000 | 0.8217          | 0.3307 | 0.3202    |
+| 0.0001        | 103.4561 | 3000 | 0.8547          | 0.3325 | 0.3239    |
+| 0.0001        | 137.9474 | 4000 | 0.8674          | 0.3344 | 0.3270    |
+
+
+### Framework versions
+
+- Transformers 4.51.3
+- Pytorch 2.7.0+cu126
+- Datasets 3.5.1
+- Tokenizers 0.21.1

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