automatic-speech-recognition common_voice generated_from_trainer

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wav2vec2-liepa-1-percent

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the COMMON_VOICE - LT dataset. It achieves the following results on the evaluation set:

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

Training results

Training Loss Epoch Step Validation Loss Wer
No log 0.23 100 3.3596 1.0
No log 0.46 200 2.9280 1.0
No log 0.69 300 1.5091 0.9650
No log 0.93 400 0.9943 0.9177
3.1184 1.16 500 0.7590 0.7793
3.1184 1.39 600 0.7336 0.7408
3.1184 1.62 700 0.7040 0.7618
3.1184 1.85 800 0.6815 0.7233
3.1184 2.08 900 0.6457 0.6865
0.7917 2.31 1000 0.5705 0.6813
0.7917 2.55 1100 0.5708 0.6620
0.7917 2.78 1200 0.5888 0.6462
0.7917 3.01 1300 0.6509 0.6970
0.7917 3.24 1400 0.5871 0.6462
0.5909 3.47 1500 0.6199 0.6813
0.5909 3.7 1600 0.6230 0.5919
0.5909 3.94 1700 0.5721 0.6427
0.5909 4.17 1800 0.5331 0.5867
0.5909 4.4 1900 0.5561 0.6007
0.4607 4.63 2000 0.5414 0.5849
0.4607 4.86 2100 0.5390 0.5587
0.4607 5.09 2200 0.5313 0.5569
0.4607 5.32 2300 0.5893 0.5797
0.4607 5.56 2400 0.5507 0.5954
0.3933 5.79 2500 0.5521 0.6025
0.3933 6.02 2600 0.5663 0.5989
0.3933 6.25 2700 0.5636 0.5832
0.3933 6.48 2800 0.5464 0.5919
0.3933 6.71 2900 0.5623 0.5832
0.3367 6.94 3000 0.5324 0.5692
0.3367 7.18 3100 0.5907 0.5394
0.3367 7.41 3200 0.5653 0.5814
0.3367 7.64 3300 0.5707 0.5814
0.3367 7.87 3400 0.5754 0.5429
0.2856 8.1 3500 0.5953 0.5569
0.2856 8.33 3600 0.6275 0.5394
0.2856 8.56 3700 0.6253 0.5569
0.2856 8.8 3800 0.5930 0.5429
0.2856 9.03 3900 0.6082 0.5219
0.2522 9.26 4000 0.6026 0.5447
0.2522 9.49 4100 0.6052 0.5271
0.2522 9.72 4200 0.5871 0.5219
0.2522 9.95 4300 0.5870 0.5236
0.2522 10.19 4400 0.5881 0.5131
0.2167 10.42 4500 0.6122 0.5289
0.2167 10.65 4600 0.6128 0.5166
0.2167 10.88 4700 0.6135 0.5377
0.2167 11.11 4800 0.6055 0.5184
0.2167 11.34 4900 0.6725 0.5569
0.1965 11.57 5000 0.6482 0.5429
0.1965 11.81 5100 0.6037 0.5096
0.1965 12.04 5200 0.5931 0.5131
0.1965 12.27 5300 0.5853 0.5114
0.1965 12.5 5400 0.5798 0.5219
0.172 12.73 5500 0.5775 0.5009
0.172 12.96 5600 0.5782 0.5044
0.172 13.19 5700 0.5804 0.5184
0.172 13.43 5800 0.5977 0.5219
0.172 13.66 5900 0.6069 0.5236
0.1622 13.89 6000 0.5850 0.5131
0.1622 14.12 6100 0.5758 0.5096
0.1622 14.35 6200 0.5752 0.5009
0.1622 14.58 6300 0.5727 0.5184
0.1622 14.81 6400 0.5795 0.5044

Framework versions