Create README.md

README.md

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+---
+language:
+- te
+license: apache-2.0
+tags:
+- hf-asr-leaderboard
+- generated_from_trainer
+datasets:
+- IndicSUPERB_train_validation_splits
+metrics:
+- wer
+model-index:
+- name: Whisper Small Telugu - Naga Budigam
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: IndicSUPERB train and validation splits
+      type: IndicSUPERB train and validation splits
+      config: None
+      split: None
+      args: 'config: te, split: test'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 38.14924740301039
+---
+
+<!-- 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 - Naga Budigam
+
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Chai_Bisket_Stories_16-08-2021_14-17 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2875
+- Wer: 38.1492
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- 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: 500
+- training_steps: 15000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Wer     |
+|:-------------:|:-----:|:-----:|:---------------:|:-------:|
+| 0.2064        | 0.66  | 500   | 0.2053          | 60.1707 |
+| 0.1399        | 1.33  | 1000  | 0.1535          | 49.3269 |
+| 0.1093        | 1.99  | 1500  | 0.1365          | 44.5516 |
+| 0.0771        | 2.66  | 2000  | 0.1316          | 42.1136 |
+| 0.0508        | 3.32  | 2500  | 0.1395          | 41.1384 |
+| 0.0498        | 3.99  | 3000  | 0.1386          | 40.5395 |
+| 0.0302        | 4.65  | 3500  | 0.1529          | 40.9529 |
+| 0.0157        | 5.32  | 4000  | 0.1719          | 40.6667 |
+| 0.0183        | 5.98  | 4500  | 0.1723          | 40.3646 |
+| 0.0083        | 6.65  | 5000  | 0.1911          | 40.4335 |
+| 0.0061        | 7.31  | 5500  | 0.2109          | 40.4176 |
+| 0.0055        | 7.98  | 6000  | 0.2075          | 39.7021 |
+| 0.0039        | 8.64  | 6500  | 0.2186          | 40.2639 |
+| 0.0026        | 9.31  | 7000  | 0.2254          | 39.1032 |
+| 0.0035        | 9.97  | 7500  | 0.2289          | 39.2834 |
+| 0.0016        | 10.64 | 8000  | 0.2332          | 39.1456 |
+| 0.0016        | 11.3  | 8500  | 0.2395          | 39.4371 |
+| 0.0016        | 11.97 | 9000  | 0.2447          | 39.2410 |
+| 0.0009        | 12.63 | 9500  | 0.2548          | 38.7799 |
+| 0.0008        | 13.3  | 10000 | 0.2551          | 38.7481 |
+| 0.0008        | 13.96 | 10500 | 0.2621          | 38.8276 |
+| 0.0007        | 14.63 | 11000 | 0.2633          | 38.6686 |
+| 0.0003        | 15.29 | 11500 | 0.2711          | 38.4566 |
+| 0.0005        | 15.96 | 12000 | 0.2772          | 38.7852 |
+| 0.0001        | 16.62 | 12500 | 0.2771          | 38.2658 |
+| 0.0001        | 17.29 | 13000 | 0.2808          | 38.2393 |
+| 0.0001        | 17.95 | 13500 | 0.2815          | 38.1810 |
+| 0.0           | 18.62 | 14000 | 0.2854          | 38.2022 |
+| 0.0           | 19.28 | 14500 | 0.2872          | 38.1333 |
+| 0.0           | 19.95 | 15000 | 0.2875          | 38.1492 |
+
+
+### Framework versions
+
+- Transformers 4.26.0.dev0
+- Pytorch 1.13.0
+- Datasets 2.7.1
+- Tokenizers 0.13.2