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kiranpantha
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whisper-base-ne

Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Nepali
whisper
Generated from Trainer
Eval Results
Inference Endpoints
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End of training

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  1. README.md +15 -15
README.md CHANGED
@@ -25,7 +25,7 @@ model-index:
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  metrics:
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  - name: Wer
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  type: wer
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- value: 70.95343680709534
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -35,8 +35,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the OpenSLR54 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8516
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- - Wer: 70.9534
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  ## Model description
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Wer |
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- |:-------------:|:-------:|:----:|:---------------:|:-------:|
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- | 0.4095 | 2.9940 | 500 | 0.5248 | 82.9268 |
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- | 0.0953 | 5.9880 | 1000 | 0.5482 | 75.8315 |
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- | 0.0164 | 8.9820 | 1500 | 0.6417 | 73.8359 |
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- | 0.004 | 11.9760 | 2000 | 0.7480 | 73.8359 |
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- | 0.0005 | 14.9701 | 2500 | 0.7697 | 71.8404 |
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- | 0.0002 | 17.9641 | 3000 | 0.8008 | 71.6186 |
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- | 0.0002 | 20.9581 | 3500 | 0.8219 | 71.3969 |
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- | 0.0001 | 23.9521 | 4000 | 0.8370 | 70.7317 |
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- | 0.0001 | 26.9461 | 4500 | 0.8476 | 70.7317 |
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- | 0.0001 | 29.9401 | 5000 | 0.8516 | 70.9534 |
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  ### Framework versions
 
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  metrics:
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  - name: Wer
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  type: wer
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+ value: 43.58105012370567
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the OpenSLR54 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2096
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+ - Wer: 43.5811
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:------:|:----:|:---------------:|:-------:|
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+ | 0.5243 | 0.1200 | 500 | 0.4983 | 77.1832 |
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+ | 0.3685 | 0.2399 | 1000 | 0.3600 | 64.9684 |
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+ | 0.3007 | 0.3599 | 1500 | 0.3094 | 58.0592 |
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+ | 0.2704 | 0.4798 | 2000 | 0.2785 | 54.5038 |
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+ | 0.2529 | 0.5998 | 2500 | 0.2560 | 50.7560 |
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+ | 0.2479 | 0.7198 | 3000 | 0.2407 | 48.4193 |
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+ | 0.2349 | 0.8397 | 3500 | 0.2262 | 46.3850 |
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+ | 0.211 | 0.9597 | 4000 | 0.2170 | 45.2305 |
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+ | 0.1707 | 1.0797 | 4500 | 0.2132 | 44.6990 |
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+ | 0.1506 | 1.1996 | 5000 | 0.2096 | 43.5811 |
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  ### Framework versions