update model card README.md

README.md

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+---
+language:
+- bn
+license: apache-2.0
+base_model: openai/whisper-small
+tags:
+- generated_from_trainer
+datasets:
+- mozilla-foundation/common_voice_13_0
+metrics:
+- wer
+model-index:
+- name: Whisper in Bangla
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 13
+      type: mozilla-foundation/common_voice_13_0
+      config: bn
+      split: test
+      args: bn
+    metrics:
+    - name: Wer
+      type: wer
+      value: 36.383706024782796
+---
+
+<!-- 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 in Bangla
+
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1242
+- Wer: 36.3837
+
+## 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: 1000
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| 0.0544        | 0.27  | 500  | 0.1283          | 37.4448 |
+| 0.0526        | 0.53  | 1000 | 0.1242          | 36.3837 |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.0
+- Datasets 2.14.2
+- Tokenizers 0.13.3