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arslanarjumand
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wav2vec-reptiles

Audio Classification
Transformers
Safetensors
wav2vec2-bert
Generated from Trainer
Inference Endpoints
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arslanarjumand/wav2vec-reptiles

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  1. README.md +14 -14
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -15,11 +15,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 484.9289
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- - Pcc Accuracy: -0.1604
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- - Pcc Fluency: -0.1393
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- - Pcc Total Score: -0.1591
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- - Pcc Content: -0.1544
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  ## Model description
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@@ -54,15 +54,15 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Pcc Accuracy | Pcc Fluency | Pcc Total Score | Pcc Content |
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  |:-------------:|:-----:|:----:|:---------------:|:------------:|:-----------:|:---------------:|:-----------:|
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- | 3175.5941 | 1.07 | 500 | 2802.1936 | -0.2863 | -0.2729 | -0.3001 | -0.2745 |
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- | 1733.457 | 2.13 | 1000 | 2440.8833 | -0.2827 | -0.2779 | -0.2959 | -0.2787 |
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- | 1890.6879 | 3.2 | 1500 | 1470.4958 | -0.2806 | -0.2763 | -0.2933 | -0.2772 |
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- | 470.8979 | 4.27 | 2000 | 565.3928 | -0.2658 | -0.2589 | -0.2764 | -0.2621 |
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- | 881.7893 | 5.34 | 2500 | 501.9731 | -0.2331 | -0.2204 | -0.2394 | -0.2285 |
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- | 379.352 | 6.4 | 3000 | 497.4395 | -0.2040 | -0.1871 | -0.2068 | -0.1982 |
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- | 378.5915 | 7.47 | 3500 | 491.6927 | -0.1783 | -0.1590 | -0.1789 | -0.1726 |
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- | 539.6395 | 8.54 | 4000 | 487.6133 | -0.1639 | -0.1434 | -0.1631 | -0.1582 |
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- | 319.019 | 9.61 | 4500 | 484.9289 | -0.1604 | -0.1393 | -0.1591 | -0.1544 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 483.1183
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+ - Pcc Accuracy: -0.0911
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+ - Pcc Fluency: -0.0702
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+ - Pcc Total Score: -0.0823
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+ - Pcc Content: -0.0799
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Pcc Accuracy | Pcc Fluency | Pcc Total Score | Pcc Content |
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  |:-------------:|:-----:|:----:|:---------------:|:------------:|:-----------:|:---------------:|:-----------:|
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+ | 3259.2658 | 1.07 | 500 | 2804.9829 | -0.2619 | -0.2376 | -0.2620 | -0.2464 |
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+ | 1980.8576 | 2.13 | 1000 | 2444.1970 | -0.2591 | -0.2359 | -0.2573 | -0.2394 |
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+ | 1728.8568 | 3.2 | 1500 | 1480.2877 | -0.2539 | -0.2310 | -0.2519 | -0.2337 |
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+ | 490.517 | 4.27 | 2000 | 577.7591 | -0.2334 | -0.2102 | -0.2303 | -0.2141 |
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+ | 761.9771 | 5.34 | 2500 | 503.8331 | -0.1885 | -0.1646 | -0.1829 | -0.1714 |
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+ | 286.5463 | 6.4 | 3000 | 496.2837 | -0.1460 | -0.1234 | -0.1390 | -0.1315 |
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+ | 341.2555 | 7.47 | 3500 | 488.9790 | -0.1150 | -0.0937 | -0.1072 | -0.1026 |
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+ | 544.4691 | 8.54 | 4000 | 484.3144 | -0.0955 | -0.0745 | -0.0870 | -0.0841 |
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+ | 377.6802 | 9.61 | 4500 | 483.1183 | -0.0911 | -0.0702 | -0.0823 | -0.0799 |
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  ### Framework versions
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