update model card README.md

README.md

@@ -0,0 +1,79 @@
+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- speech_commands
+metrics:
+- wer
+model-index:
+- name: whisper-small-Eng-1
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: speech_commands
+      type: speech_commands
+      config: v0.01
+      split: test
+      args: v0.01
+    metrics:
+    - name: Wer
+      type: wer
+      value: 239.6
+---
+
+<!-- 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-Eng-1
+
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the speech_commands dataset.
+It achieves the following results on the evaluation set:
+- Loss: 5.0620
+- Wer: 239.6
+
+## 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: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 4
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 5
+- training_steps: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer   |
+|:-------------:|:-----:|:----:|:---------------:|:-----:|
+| 7.156         | 0.01  | 5    | 6.9727          | 256.4 |
+| 7.5392        | 0.02  | 10   | 5.0620          | 239.6 |
+
+
+### Framework versions
+
+- Transformers 4.28.0
+- Pytorch 2.0.0+cu118
+- Datasets 2.12.0
+- Tokenizers 0.13.3