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scanne
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addison6

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
wav2vec2
Generated from Trainer
Inference Endpoints
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update model card README.md

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@@ -14,8 +14,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.8211
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- - Wer: 0.3999
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  ## Model description
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@@ -48,34 +48,35 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:-----:|:-----:|:---------------:|:------:|
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- | 4.0858 | 1.04 | 500 | 2.8986 | 0.9999 |
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- | 1.8903 | 2.08 | 1000 | 1.3421 | 0.7280 |
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- | 1.2374 | 3.12 | 1500 | 1.0214 | 0.6037 |
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- | 0.9979 | 4.16 | 2000 | 1.2212 | 0.5556 |
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- | 0.8648 | 5.2 | 2500 | 1.2449 | 0.5222 |
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- | 0.7663 | 6.24 | 3000 | 1.0319 | 0.4734 |
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- | 0.6672 | 7.28 | 3500 | 1.3437 | 0.4786 |
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- | 0.6224 | 8.32 | 4000 | 1.3717 | 0.4667 |
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- | 0.5785 | 9.36 | 4500 | 1.2714 | 0.4374 |
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- | 0.5133 | 10.4 | 5000 | 1.4949 | 0.4508 |
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- | 0.4963 | 11.43 | 5500 | 1.3073 | 0.4260 |
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- | 0.4455 | 12.47 | 6000 | 1.4153 | 0.4375 |
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- | 0.4279 | 13.51 | 6500 | 1.3283 | 0.4164 |
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- | 0.415 | 14.55 | 7000 | 1.4219 | 0.4335 |
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- | 0.384 | 15.59 | 7500 | 1.5668 | 0.4150 |
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- | 0.369 | 16.63 | 8000 | 1.6059 | 0.4096 |
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- | 0.3415 | 17.67 | 8500 | 1.4167 | 0.4301 |
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- | 0.3358 | 18.71 | 9000 | 1.5522 | 0.4258 |
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- | 0.3089 | 19.75 | 9500 | 1.5970 | 0.4185 |
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- | 0.2934 | 20.79 | 10000 | 1.7218 | 0.4350 |
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- | 0.2714 | 21.83 | 10500 | 1.6608 | 0.4174 |
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- | 0.2396 | 22.87 | 11000 | 1.6413 | 0.4100 |
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- | 0.2346 | 23.91 | 11500 | 1.7355 | 0.4001 |
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- | 0.2171 | 24.95 | 12000 | 1.7991 | 0.3980 |
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- | 0.1981 | 25.99 | 12500 | 1.7772 | 0.4037 |
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- | 0.1952 | 27.03 | 13000 | 1.7544 | 0.4016 |
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- | 0.1812 | 28.07 | 13500 | 1.8241 | 0.4012 |
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- | 0.168 | 29.11 | 14000 | 1.8211 | 0.3999 |
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.4278
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+ - Wer: 0.3784
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:-----:|:-----:|:---------------:|:------:|
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+ | 4.0707 | 1.03 | 500 | 2.8972 | 0.9998 |
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+ | 1.8869 | 2.05 | 1000 | 1.3286 | 0.6772 |
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+ | 1.218 | 3.08 | 1500 | 1.0999 | 0.5714 |
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+ | 1.0183 | 4.11 | 2000 | 1.0781 | 0.5523 |
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+ | 0.8743 | 5.13 | 2500 | 0.9991 | 0.4951 |
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+ | 0.7561 | 6.16 | 3000 | 1.0861 | 0.4869 |
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+ | 0.6883 | 7.19 | 3500 | 1.1915 | 0.4704 |
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+ | 0.6185 | 8.21 | 4000 | 1.1553 | 0.4634 |
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+ | 0.5761 | 9.24 | 4500 | 1.1144 | 0.4513 |
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+ | 0.5315 | 10.27 | 5000 | 1.1818 | 0.4298 |
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+ | 0.4982 | 11.29 | 5500 | 1.1973 | 0.4329 |
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+ | 0.4719 | 12.32 | 6000 | 1.1456 | 0.4259 |
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+ | 0.4369 | 13.35 | 6500 | 1.1701 | 0.4292 |
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+ | 0.4083 | 14.37 | 7000 | 1.1929 | 0.4132 |
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+ | 0.3886 | 15.4 | 7500 | 1.3307 | 0.4163 |
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+ | 0.3752 | 16.43 | 8000 | 1.3405 | 0.4081 |
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+ | 0.349 | 17.45 | 8500 | 1.3283 | 0.3952 |
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+ | 0.3261 | 18.48 | 9000 | 1.2956 | 0.4128 |
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+ | 0.3094 | 19.51 | 9500 | 1.2671 | 0.4004 |
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+ | 0.3041 | 20.53 | 10000 | 1.3534 | 0.3964 |
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+ | 0.2796 | 21.56 | 10500 | 1.3730 | 0.3899 |
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+ | 0.25 | 22.59 | 11000 | 1.3952 | 0.3942 |
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+ | 0.2303 | 23.61 | 11500 | 1.4792 | 0.3923 |
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+ | 0.2321 | 24.64 | 12000 | 1.4228 | 0.3847 |
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+ | 0.2 | 25.67 | 12500 | 1.4469 | 0.3837 |
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+ | 0.2009 | 26.69 | 13000 | 1.4532 | 0.3820 |
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+ | 0.195 | 27.72 | 13500 | 1.4329 | 0.3821 |
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+ | 0.1804 | 28.75 | 14000 | 1.4265 | 0.3799 |
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+ | 0.1713 | 29.77 | 14500 | 1.4278 | 0.3784 |
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  ### Framework versions