update model card README.md

README.md

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+---
+language:
+- bn
+license: apache-2.0
+base_model: openai/whisper-small
+tags:
+- hf-asr-leaderboard
+- generated_from_trainer
+datasets:
+- bengaliAI-kaggle
+metrics:
+- wer
+model-index:
+- name: whisper-small fintuned-0-10000-50%
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: bengaliAI-kaggle
+      type: bengaliAI-kaggle
+      args: 'config: bn, split: test'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 90.44179607559889
+---
+
+<!-- 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 fintuned-0-10000-50%
+
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the bengaliAI-kaggle dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6193
+- Wer: 90.4418
+
+## 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: 4
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 50
+- training_steps: 200
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer      |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.8424        | 0.4   | 100  | 0.7538          | 103.2021 |
+| 0.6195        | 0.8   | 200  | 0.6193          | 90.4418  |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.0
+- Datasets 2.14.4
+- Tokenizers 0.13.3