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JacobLinCool
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wft-test-model-merged

Automatic Speech Recognition
Transformers
Safetensors
English
whisper
wft
audio
speech
Generated from Trainer
Eval Results (legacy)
Model card Files
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@@ -37,12 +37,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the hf-internal-testing/librispeech_asr_dummy dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1218
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  - Wer: 4.7244
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- - Cer: 100.7102
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- - Decode Time: 0.5595
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- - Wer Time: 0.0060
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- - Cer Time: 0.0027
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Decode Time | Wer Time | Cer Time |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|:--------:|:--------:|
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- | 2.4038 | 0.1 | 10 | 1.9871 | 299.6063 | 116.5483 | 0.5542 | 0.0112 | 0.0038 |
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- | 1.2202 | 1.01 | 20 | 1.1610 | 172.0472 | 91.6903 | 0.5178 | 0.0055 | 0.0028 |
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- | 0.8765 | 1.11 | 30 | 0.8079 | 31.8898 | 56.1080 | 0.4854 | 0.0051 | 0.0024 |
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- | 0.4415 | 2.02 | 40 | 0.6279 | 25.9843 | 82.5284 | 0.5218 | 0.0060 | 0.0028 |
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- | 0.4307 | 2.12 | 50 | 0.4509 | 16.9291 | 98.2955 | 0.5377 | 0.0056 | 0.0030 |
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- | 0.2363 | 3.03 | 60 | 0.2952 | 9.4488 | 102.9119 | 0.5310 | 0.0048 | 0.0027 |
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- | 0.2245 | 3.13 | 70 | 0.2046 | 7.4803 | 96.3778 | 0.5429 | 0.0056 | 0.0029 |
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- | 0.1053 | 4.04 | 80 | 0.1700 | 5.5118 | 96.4489 | 0.5306 | 0.0067 | 0.0028 |
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- | 0.0731 | 4.14 | 90 | 0.1320 | 4.7244 | 97.1591 | 0.5509 | 0.0050 | 0.0026 |
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- | 0.0782 | 5.05 | 100 | 0.1218 | 4.7244 | 100.7102 | 0.5595 | 0.0060 | 0.0027 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the hf-internal-testing/librispeech_asr_dummy dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1248
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  - Wer: 4.7244
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+ - Cer: 92.6847
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+ - Decode Time: 0.5481
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+ - Wer Time: 0.0069
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+ - Cer Time: 0.0040
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Decode Time | Wer Time | Cer Time |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|:--------:|:--------:|
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+ | 2.4107 | 0.1 | 10 | 1.9892 | 303.5433 | 117.1875 | 0.5449 | 0.0307 | 0.0039 |
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+ | 1.2109 | 1.01 | 20 | 1.1659 | 155.1181 | 91.2642 | 0.5278 | 0.0062 | 0.0036 |
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+ | 0.8855 | 1.11 | 30 | 0.8104 | 30.7087 | 56.8182 | 0.4832 | 0.0069 | 0.0041 |
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+ | 0.4367 | 2.02 | 40 | 0.6315 | 25.1969 | 74.5739 | 0.5295 | 0.0058 | 0.0034 |
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+ | 0.4398 | 2.12 | 50 | 0.4566 | 17.3228 | 91.9744 | 0.6078 | 0.0055 | 0.0030 |
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+ | 0.2291 | 3.03 | 60 | 0.3006 | 9.0551 | 100.7102 | 0.5659 | 0.0058 | 0.0031 |
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+ | 0.2281 | 3.13 | 70 | 0.2144 | 7.4803 | 90.4830 | 0.5507 | 0.0046 | 0.0030 |
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+ | 0.111 | 4.04 | 80 | 0.1736 | 5.9055 | 89.3466 | 0.6595 | 0.0063 | 0.0032 |
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+ | 0.0695 | 4.14 | 90 | 0.1345 | 4.7244 | 87.9261 | 0.6369 | 0.0402 | 0.0182 |
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+ | 0.0761 | 5.05 | 100 | 0.1248 | 4.7244 | 92.6847 | 0.5481 | 0.0069 | 0.0040 |
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  ### Framework versions