update model card README.md

README.md

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+---
+license: apache-2.0
+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
+      config: en-US
+      split: train[450:]
+      args: en-US
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.34415584415584416
+---
+
+<!-- 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: 0.6314
+- Wer Ortho: 0.3473
+- Wer: 0.3442
+
+## 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: 16
+- eval_batch_size: 16
+- 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: 500
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
+| 0.001         | 17.86 | 500  | 0.6314          | 0.3473    | 0.3442 |
+
+
+### Framework versions
+
+- Transformers 4.29.2
+- Pytorch 2.0.1
+- Datasets 2.12.0
+- Tokenizers 0.13.2