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End of training

Browse files
README.md CHANGED
@@ -23,7 +23,7 @@ model-index:
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  metrics:
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  - name: Wer
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  type: wer
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- value: 0.9372822299651568
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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
@@ -33,9 +33,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the audiofolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.4927
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- - Wer: 0.9373
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- - Cer: 0.4631
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  ## Model description
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@@ -70,22 +70,22 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
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- | 11.1283 | 6.25 | 100 | 7.6957 | 1.0 | 1.0 |
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- | 3.4765 | 12.5 | 200 | 3.0361 | 1.0 | 1.0 |
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- | 3.0411 | 18.75 | 300 | 2.9111 | 1.0 | 1.0 |
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- | 2.9832 | 25.0 | 400 | 2.8719 | 1.0 | 1.0 |
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- | 2.9412 | 31.25 | 500 | 2.8650 | 1.0 | 1.0 |
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- | 2.9002 | 37.5 | 600 | 2.8412 | 1.0 | 1.0 |
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- | 2.9023 | 43.75 | 700 | 2.8232 | 1.0 | 1.0 |
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- | 2.7997 | 50.0 | 800 | 2.6466 | 1.0 | 0.9985 |
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- | 2.7052 | 56.25 | 900 | 2.4730 | 1.0 | 0.9863 |
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- | 2.5173 | 62.5 | 1000 | 2.2351 | 1.0 | 0.9337 |
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- | 2.3026 | 68.75 | 1100 | 1.9446 | 0.9721 | 0.7403 |
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- | 2.1178 | 75.0 | 1200 | 1.7418 | 0.9756 | 0.5903 |
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- | 1.9672 | 81.25 | 1300 | 1.5979 | 0.9477 | 0.5217 |
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- | 1.891 | 87.5 | 1400 | 1.5311 | 0.9443 | 0.4958 |
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- | 1.827 | 93.75 | 1500 | 1.4928 | 0.9443 | 0.4714 |
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- | 1.8131 | 100.0 | 1600 | 1.4927 | 0.9373 | 0.4631 |
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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: 0.5749128919860628
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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 [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the audiofolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.0281
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+ - Wer: 0.5749
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+ - Cer: 0.2049
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
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+ | 9.4495 | 6.25 | 100 | 4.3525 | 1.0 | 1.0 |
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+ | 3.1633 | 12.5 | 200 | 2.9339 | 1.0 | 1.0 |
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+ | 2.964 | 18.75 | 300 | 2.8446 | 1.0 | 1.0 |
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+ | 2.8489 | 25.0 | 400 | 2.6748 | 1.0 | 1.0 |
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+ | 2.409 | 31.25 | 500 | 1.9297 | 1.0 | 0.6824 |
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+ | 1.6654 | 37.5 | 600 | 1.3226 | 0.9024 | 0.3686 |
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+ | 1.2589 | 43.75 | 700 | 1.0957 | 0.7666 | 0.2749 |
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+ | 1.0072 | 50.0 | 800 | 1.0241 | 0.6585 | 0.2445 |
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+ | 0.818 | 56.25 | 900 | 1.0104 | 0.6132 | 0.2239 |
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+ | 0.7072 | 62.5 | 1000 | 0.9941 | 0.5923 | 0.2155 |
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+ | 0.5998 | 68.75 | 1100 | 1.0503 | 0.5749 | 0.2079 |
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+ | 0.5677 | 75.0 | 1200 | 1.0376 | 0.5784 | 0.2049 |
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+ | 0.5125 | 81.25 | 1300 | 1.0549 | 0.5819 | 0.2133 |
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+ | 0.4983 | 87.5 | 1400 | 1.0222 | 0.5505 | 0.1988 |
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+ | 0.4859 | 93.75 | 1500 | 1.0176 | 0.5575 | 0.1995 |
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+ | 0.4436 | 100.0 | 1600 | 1.0281 | 0.5749 | 0.2049 |
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  ### Framework versions
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