update model card README.md

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- afrispeech-200
+metrics:
+- wer
+model-index:
+- name: whisper-small-hi-2400_500_136
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: afrispeech-200
+      type: afrispeech-200
+      config: hausa
+      split: train
+      args: hausa
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.31118587047939444
+---
+
+<!-- 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-small-hi-2400_500_136
+
+This model is a fine-tuned version of [saif-daoud/whisper-small-hi-2400_500_135](https://huggingface.co/saif-daoud/whisper-small-hi-2400_500_135) on the afrispeech-200 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7547
+- Wer: 0.3112
+
+## 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-07
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 400
+- training_steps: 1362
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 0.7162        | 0.5   | 681  | 0.7551          | 0.3118 |
+| 0.7109        | 1.5   | 1362 | 0.7547          | 0.3112 |
+
+
+### Framework versions
+
+- Transformers 4.28.0.dev0
+- Pytorch 1.13.1+cu116
+- Datasets 2.11.0
+- Tokenizers 0.13.2