End of training

README.md

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+---
+license: apache-2.0
+base_model: openai/whisper-tiny
+tags:
+- generated_from_trainer
+datasets:
+- PolyAI/minds14
+metrics:
+- wer
+model-index:
+- name: whisper-tiny-polyai-enUS_lower_lr
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: PolyAI/minds14
+      type: PolyAI/minds14
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.38488783943329397
+---
+
+<!-- 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_lower_lr
+
+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: 0.7730
+- Wer Ortho: 0.4022
+- Wer: 0.3849
+
+## 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_ratio: 0.1
+- training_steps: 500
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
+| 2.9571        | 3.33  | 50   | 1.9622          | 0.5077    | 0.4050 |
+| 0.5131        | 6.67  | 100  | 0.6540          | 0.4152    | 0.3684 |
+| 0.2572        | 10.0  | 150  | 0.6091          | 0.3874    | 0.3524 |
+| 0.0974        | 13.33 | 200  | 0.6316          | 0.3745    | 0.3442 |
+| 0.0405        | 16.67 | 250  | 0.6686          | 0.3917    | 0.3577 |
+| 0.0116        | 20.0  | 300  | 0.7097          | 0.4028    | 0.3766 |
+| 0.0049        | 23.33 | 350  | 0.7341          | 0.3954    | 0.3743 |
+| 0.0032        | 26.67 | 400  | 0.7510          | 0.4065    | 0.3884 |
+| 0.0023        | 30.0  | 450  | 0.7607          | 0.3967    | 0.3778 |
+| 0.0018        | 33.33 | 500  | 0.7730          | 0.4022    | 0.3849 |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.0

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+}

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