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README.md

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+---
+language:
+- hi
+license: apache-2.0
+base_model: openai/whisper-base
+tags:
+- hf-asr-leaderboard
+- generated_from_trainer
+datasets:
+- google/fleurs
+metrics:
+- wer
+model-index:
+- name: Whisper Base Hi - Samveg Bhansali
+  results: []
+---
+
+<!-- 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 Base Hi - Samveg Bhansali
+
+This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Google Fleurs  dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5117
+- Wer: 37.9539
+
+## 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
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 4000
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| 0.1401        | 4.72  | 1000 | 0.3607          | 39.9494 |
+| 0.0174        | 9.43  | 2000 | 0.4239          | 38.9954 |
+| 0.0022        | 14.15 | 3000 | 0.4867          | 38.4698 |
+| 0.001         | 18.87 | 4000 | 0.5117          | 37.9539 |
+
+
+### Framework versions
+
+- Transformers 4.32.0.dev0
+- Pytorch 2.0.1+cu118
+- Datasets 2.13.1
+- Tokenizers 0.13.3