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FelixK7
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whisper-medium-lv

Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Latvian
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Model card Files
xet
Metrics Community
FelixK7 commited on
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End of training

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  1. README.md +30 -30
README.md CHANGED
@@ -26,7 +26,7 @@ model-index:
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  metrics:
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  - name: Wer
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  type: wer
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- value: 67.95180722891565
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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
@@ -36,8 +36,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 17.0 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.1313
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- - Wer: 67.9518
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  ## Model description
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@@ -70,33 +70,33 @@ The following hyperparameters were used during training:
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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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- | No log | 23.0009 | 200 | 0.9920 | 47.2289 |
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- | 1.4829 | 47.0001 | 400 | 0.7982 | 48.9157 |
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- | 0.046 | 70.001 | 600 | 0.9576 | 51.3253 |
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- | 0.011 | 94.0002 | 800 | 0.9129 | 49.3976 |
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- | 0.0057 | 117.0011 | 1000 | 0.9789 | 51.3253 |
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- | 0.0057 | 141.0003 | 1200 | 1.0248 | 51.8072 |
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- | 0.005 | 164.0012 | 1400 | 1.0504 | 53.4940 |
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- | 0.0021 | 188.0004 | 1600 | 1.0447 | 67.9518 |
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- | 0.0015 | 211.0013 | 1800 | 1.0433 | 73.2530 |
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- | 0.0012 | 235.0005 | 2000 | 1.0646 | 55.1807 |
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- | 0.0012 | 258.0014 | 2200 | 1.1244 | 53.7349 |
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- | 0.0007 | 282.0006 | 2400 | 1.1156 | 59.5181 |
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- | 0.0006 | 305.0015 | 2600 | 1.1081 | 58.5542 |
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- | 0.0009 | 329.0007 | 2800 | 1.0342 | 54.4578 |
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- | 0.0006 | 352.0016 | 3000 | 1.0215 | 50.8434 |
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- | 0.0006 | 376.0008 | 3200 | 1.0619 | 56.6265 |
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- | 0.0004 | 399.0017 | 3400 | 1.1083 | 55.4217 |
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- | 0.0003 | 423.0009 | 3600 | 1.0970 | 56.8675 |
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- | 0.0006 | 447.0001 | 3800 | 1.1047 | 59.0361 |
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- | 0.0003 | 470.001 | 4000 | 1.1033 | 56.1446 |
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- | 0.0003 | 494.0002 | 4200 | 1.1003 | 57.5904 |
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- | 0.0002 | 517.0011 | 4400 | 1.1133 | 68.4337 |
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- | 0.0002 | 541.0003 | 4600 | 1.1146 | 69.3976 |
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- | 0.0001 | 564.0012 | 4800 | 1.1267 | 69.8795 |
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- | 0.0001 | 588.0004 | 5000 | 1.1313 | 67.9518 |
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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: 13.506122934252765
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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-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 17.0 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1848
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+ - Wer: 13.5061
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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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+ | No log | 0.04 | 200 | 0.8471 | 30.5453 |
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+ | 1.8421 | 0.08 | 400 | 0.3571 | 27.1906 |
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+ | 0.5851 | 0.12 | 600 | 0.3146 | 23.9508 |
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+ | 0.4787 | 0.16 | 800 | 0.2913 | 23.2454 |
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+ | 0.4845 | 0.2 | 1000 | 0.2736 | 20.9388 |
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+ | 0.4845 | 0.24 | 1200 | 0.2495 | 19.1951 |
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+ | 0.4004 | 0.28 | 1400 | 0.2416 | 18.4600 |
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+ | 0.357 | 1.018 | 1600 | 0.2300 | 17.8576 |
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+ | 0.3381 | 1.058 | 1800 | 0.2261 | 17.1125 |
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+ | 0.3052 | 1.098 | 2000 | 0.2151 | 16.6013 |
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+ | 0.3052 | 1.138 | 2200 | 0.2154 | 16.1673 |
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+ | 0.2636 | 1.178 | 2400 | 0.2256 | 17.3107 |
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+ | 0.2805 | 1.218 | 2600 | 0.2059 | 15.6482 |
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+ | 0.2331 | 1.258 | 2800 | 0.2022 | 15.4599 |
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+ | 0.2245 | 1.298 | 3000 | 0.1971 | 15.0953 |
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+ | 0.2245 | 2.036 | 3200 | 0.1988 | 14.7604 |
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+ | 0.2312 | 2.076 | 3400 | 0.1941 | 14.5623 |
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+ | 0.2077 | 2.116 | 3600 | 0.1915 | 14.2175 |
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+ | 0.1923 | 2.156 | 3800 | 0.1935 | 14.4018 |
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+ | 0.2012 | 2.196 | 4000 | 0.1906 | 14.4850 |
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+ | 0.2012 | 2.2360 | 4200 | 0.1880 | 13.9302 |
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+ | 0.1694 | 2.276 | 4400 | 0.1860 | 14.1640 |
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+ | 0.1548 | 3.014 | 4600 | 0.1855 | 13.6508 |
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+ | 0.1628 | 3.054 | 4800 | 0.1850 | 13.5557 |
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+ | 0.1529 | 3.094 | 5000 | 0.1848 | 13.5061 |
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  ### Framework versions