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marinone94
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xls-r-300m-sv-robust

Automatic Speech Recognition
Transformers
PyTorch
Swedish
wav2vec2
mozilla-foundation/common_voice_9_0
Generated from Trainer
Eval Results
Inference Endpoints
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update model card README.md

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  1. README.md +38 -38
  2. wandb/run-20220127_103723-scy0vyln/files/output.log +40 -0
  3. wandb/run-20220127_103723-scy0vyln/logs/debug-internal.log +52 -0
  4. wandb/run-20220127_103723-scy0vyln/run-scy0vyln.wandb +2 -2
README.md CHANGED
@@ -1,7 +1,7 @@
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  ---
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  language:
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  - sv-SE
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- license: apache-2.0
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  tags:
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  - automatic-speech-recognition
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  - mozilla-foundation/common_voice_7_0
@@ -18,10 +18,10 @@ should probably proofread and complete it, then remove this comment. -->
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  #
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- This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - SV-SE dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3179
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- - Wer: 0.2735
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  ## Model description
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@@ -56,40 +56,40 @@ 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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- | 3.3332 | 1.45 | 500 | 3.2920 | 1.0 |
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- | 2.9269 | 2.91 | 1000 | 2.9415 | 0.9966 |
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- | 2.0719 | 4.36 | 1500 | 1.1641 | 0.8508 |
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- | 1.7404 | 5.81 | 2000 | 0.7281 | 0.6846 |
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- | 1.5921 | 7.27 | 2500 | 0.5886 | 0.5147 |
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- | 1.4941 | 8.72 | 3000 | 0.5183 | 0.5063 |
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- | 1.4486 | 10.17 | 3500 | 0.4749 | 0.4676 |
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- | 1.3899 | 11.63 | 4000 | 0.4565 | 0.4432 |
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- | 1.3881 | 13.08 | 4500 | 0.4316 | 0.4228 |
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- | 1.3572 | 14.53 | 5000 | 0.4195 | 0.3834 |
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- | 1.3261 | 15.99 | 5500 | 0.3974 | 0.3607 |
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- | 1.2809 | 17.44 | 6000 | 0.3845 | 0.3467 |
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- | 1.2713 | 18.89 | 6500 | 0.3832 | 0.3450 |
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- | 1.257 | 20.35 | 7000 | 0.3779 | 0.3373 |
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- | 1.2298 | 21.8 | 7500 | 0.3744 | 0.3391 |
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- | 1.2173 | 23.26 | 8000 | 0.3745 | 0.3262 |
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- | 1.1966 | 24.71 | 8500 | 0.3680 | 0.3241 |
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- | 1.1925 | 26.16 | 9000 | 0.3605 | 0.3171 |
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- | 1.1692 | 27.61 | 9500 | 0.3512 | 0.3147 |
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- | 1.1704 | 29.07 | 10000 | 0.3532 | 0.3098 |
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- | 1.1595 | 30.52 | 10500 | 0.3425 | 0.3039 |
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- | 1.1433 | 31.97 | 11000 | 0.3568 | 0.3026 |
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- | 1.1295 | 33.43 | 11500 | 0.3461 | 0.2992 |
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- | 1.1131 | 34.88 | 12000 | 0.3349 | 0.2942 |
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- | 1.1015 | 36.34 | 12500 | 0.3378 | 0.2961 |
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- | 1.0835 | 37.79 | 13000 | 0.3282 | 0.2865 |
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- | 1.083 | 39.24 | 13500 | 0.3182 | 0.2826 |
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- | 1.0819 | 40.7 | 14000 | 0.3264 | 0.2850 |
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- | 1.072 | 42.15 | 14500 | 0.3279 | 0.2817 |
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- | 1.0456 | 43.6 | 15000 | 0.3234 | 0.2793 |
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- | 1.0581 | 45.06 | 15500 | 0.3220 | 0.2779 |
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- | 1.0406 | 46.51 | 16000 | 0.3208 | 0.2762 |
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- | 1.0422 | 47.96 | 16500 | 0.3184 | 0.2752 |
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- | 1.0099 | 49.42 | 17000 | 0.3181 | 0.2735 |
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  ### Framework versions
 
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  ---
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  language:
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  - sv-SE
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+ license: cc0-1.0
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  tags:
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  - automatic-speech-recognition
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  - mozilla-foundation/common_voice_7_0
 
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  #
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+ This model is a fine-tuned version of [KBLab/wav2vec2-large-voxrex](https://huggingface.co/KBLab/wav2vec2-large-voxrex) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - SV-SE dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2201
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+ - Wer: 0.1778
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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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+ | 3.1522 | 1.45 | 500 | 3.1290 | 1.0 |
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+ | 2.9576 | 2.91 | 1000 | 2.9633 | 1.0 |
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+ | 1.9853 | 4.36 | 1500 | 0.8902 | 0.6104 |
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+ | 1.5867 | 5.81 | 2000 | 0.4793 | 0.3664 |
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+ | 1.4608 | 7.27 | 2500 | 0.3816 | 0.3095 |
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+ | 1.3496 | 8.72 | 3000 | 0.3415 | 0.2783 |
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+ | 1.3058 | 10.17 | 3500 | 0.3072 | 0.2519 |
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+ | 1.2533 | 11.63 | 4000 | 0.2877 | 0.2381 |
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+ | 1.2535 | 13.08 | 4500 | 0.2791 | 0.2320 |
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+ | 1.2273 | 14.53 | 5000 | 0.2726 | 0.2282 |
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+ | 1.2083 | 15.99 | 5500 | 0.2638 | 0.2212 |
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+ | 1.1606 | 17.44 | 6000 | 0.2531 | 0.2174 |
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+ | 1.1545 | 18.89 | 6500 | 0.2468 | 0.2109 |
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+ | 1.1344 | 20.35 | 7000 | 0.2494 | 0.2050 |
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+ | 1.1173 | 21.8 | 7500 | 0.2447 | 0.1980 |
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+ | 1.1081 | 23.26 | 8000 | 0.2428 | 0.1998 |
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+ | 1.1023 | 24.71 | 8500 | 0.2329 | 0.1951 |
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+ | 1.0923 | 26.16 | 9000 | 0.2388 | 0.1962 |
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+ | 1.0798 | 27.61 | 9500 | 0.2363 | 0.1944 |
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+ | 1.0769 | 29.07 | 10000 | 0.2342 | 0.1913 |
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+ | 1.0672 | 30.52 | 10500 | 0.2250 | 0.1875 |
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+ | 1.0735 | 31.97 | 11000 | 0.2305 | 0.1874 |
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+ | 1.0628 | 33.43 | 11500 | 0.2291 | 0.1851 |
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+ | 1.0451 | 34.88 | 12000 | 0.2263 | 0.1856 |
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+ | 1.0299 | 36.34 | 12500 | 0.2257 | 0.1834 |
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+ | 1.0368 | 37.79 | 13000 | 0.2230 | 0.1808 |
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+ | 1.0322 | 39.24 | 13500 | 0.2231 | 0.1833 |
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+ | 1.0451 | 40.7 | 14000 | 0.2197 | 0.1817 |
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+ | 1.0304 | 42.15 | 14500 | 0.2241 | 0.1813 |
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+ | 1.0102 | 43.6 | 15000 | 0.2233 | 0.1795 |
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+ | 1.0135 | 45.06 | 15500 | 0.2200 | 0.1794 |
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+ | 1.014 | 46.51 | 16000 | 0.2207 | 0.1779 |
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+ | 1.0071 | 47.96 | 16500 | 0.2205 | 0.1784 |
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+ | 0.9729 | 49.42 | 17000 | 0.2204 | 0.1777 |
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  ### Framework versions
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