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bigmorning
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whisper_havest_0020

Automatic Speech Recognition
Transformers
TensorFlow
whisper
generated_from_keras_callback
Inference Endpoints
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  1. README.md +28 -26
  2. tf_model.h5 +1 -1
README.md CHANGED
@@ -14,10 +14,12 @@ 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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Train Loss: 0.1785
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- - Train Accuracy: 0.0334
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- - Validation Loss: 0.5522
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- - Validation Accuracy: 0.0314
 
 
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  - Epoch: 19
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  ## Model description
@@ -42,28 +44,28 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
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- |:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
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- | 5.0949 | 0.0116 | 4.4444 | 0.0124 | 0 |
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- | 4.3242 | 0.0130 | 4.0648 | 0.0140 | 1 |
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- | 3.9308 | 0.0145 | 3.6837 | 0.0157 | 2 |
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- | 3.5552 | 0.0159 | 3.3410 | 0.0171 | 3 |
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- | 3.1591 | 0.0175 | 2.8089 | 0.0198 | 4 |
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- | 2.2408 | 0.0221 | 1.7104 | 0.0255 | 5 |
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- | 1.4220 | 0.0261 | 1.2181 | 0.0279 | 6 |
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- | 1.0460 | 0.0280 | 0.9912 | 0.0290 | 7 |
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- | 0.8363 | 0.0291 | 0.8645 | 0.0296 | 8 |
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- | 0.6967 | 0.0299 | 0.7748 | 0.0301 | 9 |
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- | 0.5942 | 0.0305 | 0.7201 | 0.0304 | 10 |
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- | 0.5151 | 0.0309 | 0.6675 | 0.0307 | 11 |
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- | 0.4496 | 0.0314 | 0.6382 | 0.0308 | 12 |
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- | 0.3951 | 0.0318 | 0.6060 | 0.0310 | 13 |
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- | 0.3473 | 0.0321 | 0.5945 | 0.0311 | 14 |
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- | 0.3053 | 0.0324 | 0.5752 | 0.0312 | 15 |
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- | 0.2684 | 0.0327 | 0.5700 | 0.0313 | 16 |
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- | 0.2355 | 0.0330 | 0.5651 | 0.0313 | 17 |
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- | 0.2065 | 0.0332 | 0.5619 | 0.0313 | 18 |
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- | 0.1785 | 0.0334 | 0.5522 | 0.0314 | 19 |
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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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Train Loss: 4.2860
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+ - Train Accuracy: 0.0128
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+ - Train Do Wer: 1.0
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+ - Validation Loss: 4.6401
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+ - Validation Accuracy: 0.0125
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+ - Validation Do Wer: 1.0
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  - Epoch: 19
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  ## Model description
 
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  ### Training results
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+ | Train Loss | Train Accuracy | Train Do Wer | Validation Loss | Validation Accuracy | Validation Do Wer | Epoch |
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+ |:----------:|:--------------:|:------------:|:---------------:|:-------------------:|:-----------------:|:-----:|
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+ | 9.9191 | 0.0046 | 1.0 | 8.5836 | 0.0067 | 1.0 | 0 |
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+ | 8.0709 | 0.0083 | 1.0 | 7.4667 | 0.0089 | 1.0 | 1 |
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+ | 7.1652 | 0.0100 | 1.0 | 6.8204 | 0.0112 | 1.0 | 2 |
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+ | 6.7196 | 0.0114 | 1.0 | 6.5192 | 0.0114 | 1.0 | 3 |
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+ | 6.4115 | 0.0115 | 1.0 | 6.2357 | 0.0115 | 1.0 | 4 |
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+ | 6.1085 | 0.0115 | 1.0 | 5.9657 | 0.0115 | 1.0 | 5 |
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+ | 5.8206 | 0.0115 | 1.0 | 5.7162 | 0.0115 | 1.0 | 6 |
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+ | 5.5567 | 0.0115 | 1.0 | 5.4963 | 0.0115 | 1.0 | 7 |
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+ | 5.3223 | 0.0116 | 1.0 | 5.3096 | 0.0116 | 1.0 | 8 |
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+ | 5.1222 | 0.0117 | 1.0 | 5.1600 | 0.0117 | 1.0 | 9 |
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+ | 4.9580 | 0.0117 | 1.0 | 5.0391 | 0.0118 | 1.0 | 10 |
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+ | 4.8251 | 0.0119 | 1.0 | 4.9427 | 0.0118 | 1.0 | 11 |
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+ | 4.7171 | 0.0119 | 1.0 | 4.8691 | 0.0119 | 1.0 | 12 |
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+ | 4.6284 | 0.0121 | 1.0 | 4.8123 | 0.0120 | 1.0 | 13 |
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+ | 4.5508 | 0.0121 | 1.0 | 4.7620 | 0.0121 | 1.0 | 14 |
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+ | 4.4855 | 0.0123 | 1.0 | 4.7260 | 0.0121 | 1.0 | 15 |
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+ | 4.4305 | 0.0124 | 1.0 | 4.7018 | 0.0123 | 1.0 | 16 |
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+ | 4.3788 | 0.0125 | 1.0 | 4.6738 | 0.0123 | 1.0 | 17 |
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+ | 4.3305 | 0.0127 | 1.0 | 4.6525 | 0.0124 | 1.0 | 18 |
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+ | 4.2860 | 0.0128 | 1.0 | 4.6401 | 0.0125 | 1.0 | 19 |
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  ### Framework versions
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