update model card README.md

README.md

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+---
+language:
+- te
+license: apache-2.0
+tags:
+- whisper-event
+- generated_from_trainer
+datasets:
+- open slr
+metrics:
+- wer
+model-index:
+- name: whisper-small-telugu-large-data
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: open slr
+      type: open slr
+      config: null
+      split: None
+    metrics:
+    - name: Wer
+      type: wer
+      value: 123.97713870997006
+---
+
+<!-- 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-telugu-large-data
+
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the open slr and the google/fleurs datasets.
+It achieves the following results on the evaluation set:
+- Loss: 1.6348
+- Wer: 123.9771
+
+## 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: 64
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 50
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer      |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.2343        | 0.11  | 25   | 1.8167          | 116.8103 |
+| 1.9575        | 0.23  | 50   | 1.6348          | 123.9771 |
+
+
+### Framework versions
+
+- Transformers 4.25.1
+- Pytorch 1.13.0+cu117
+- Datasets 2.7.1
+- Tokenizers 0.13.2