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wav2vec2-large-xlsr-53-english-finetuned-ravdess-v6

Audio Classification
Transformers
PyTorch
wav2vec2
Generated from Trainer
Inference Endpoints
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End of training

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  1. README.md +21 -45
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-english](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-english) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.1552
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- - Accuracy: 0.5660
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  ## Model description
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@@ -52,49 +52,25 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 2.079 | 0.07 | 10 | 2.0767 | 0.1667 |
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- | 2.0728 | 0.14 | 20 | 2.0719 | 0.1389 |
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- | 2.0713 | 0.21 | 30 | 2.0576 | 0.1562 |
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- | 2.056 | 0.28 | 40 | 2.0382 | 0.1181 |
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- | 2.0759 | 0.35 | 50 | 2.0160 | 0.2778 |
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- | 2.0117 | 0.42 | 60 | 1.9332 | 0.2778 |
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- | 1.8598 | 0.49 | 70 | 1.8759 | 0.2882 |
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- | 1.9277 | 0.56 | 80 | 1.8321 | 0.2812 |
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- | 1.7897 | 0.62 | 90 | 1.7278 | 0.3819 |
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- | 1.8157 | 0.69 | 100 | 1.7270 | 0.3646 |
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- | 1.9104 | 0.76 | 110 | 1.6997 | 0.3021 |
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- | 1.8557 | 0.83 | 120 | 1.6664 | 0.4271 |
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- | 1.8803 | 0.9 | 130 | 1.7943 | 0.3021 |
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- | 1.7548 | 0.97 | 140 | 1.8016 | 0.3021 |
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- | 1.7166 | 1.04 | 150 | 1.6303 | 0.3785 |
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- | 1.7237 | 1.11 | 160 | 1.6330 | 0.4132 |
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- | 1.7228 | 1.18 | 170 | 1.5905 | 0.4306 |
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- | 1.5683 | 1.25 | 180 | 1.5216 | 0.4340 |
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- | 1.716 | 1.32 | 190 | 1.4973 | 0.4306 |
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- | 1.562 | 1.39 | 200 | 1.5994 | 0.3715 |
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- | 1.5617 | 1.46 | 210 | 1.5699 | 0.4236 |
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- | 1.6539 | 1.53 | 220 | 1.5024 | 0.3993 |
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- | 1.58 | 1.6 | 230 | 1.4787 | 0.4132 |
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- | 1.5107 | 1.67 | 240 | 1.4252 | 0.4444 |
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- | 1.5934 | 1.74 | 250 | 1.4125 | 0.4444 |
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- | 1.54 | 1.81 | 260 | 1.4032 | 0.4236 |
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- | 1.4717 | 1.88 | 270 | 1.3636 | 0.4896 |
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- | 1.5257 | 1.94 | 280 | 1.5080 | 0.4306 |
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- | 1.4537 | 2.01 | 290 | 1.3346 | 0.4757 |
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- | 1.356 | 2.08 | 300 | 1.3636 | 0.4653 |
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- | 1.3572 | 2.15 | 310 | 1.3122 | 0.4757 |
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- | 1.2657 | 2.22 | 320 | 1.2927 | 0.5174 |
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- | 1.4931 | 2.29 | 330 | 1.3161 | 0.5382 |
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- | 1.3314 | 2.36 | 340 | 1.3248 | 0.5 |
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- | 1.375 | 2.43 | 350 | 1.2859 | 0.5521 |
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- | 1.3316 | 2.5 | 360 | 1.2747 | 0.5556 |
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- | 1.1443 | 2.57 | 370 | 1.2243 | 0.5625 |
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- | 1.3866 | 2.64 | 380 | 1.2122 | 0.5590 |
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- | 1.3274 | 2.71 | 390 | 1.2192 | 0.5174 |
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- | 1.1248 | 2.78 | 400 | 1.1993 | 0.5278 |
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- | 1.1337 | 2.85 | 410 | 1.1746 | 0.5556 |
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- | 1.1394 | 2.92 | 420 | 1.1603 | 0.5625 |
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- | 1.2199 | 2.99 | 430 | 1.1553 | 0.5660 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-english](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-english) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.0166
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+ - Accuracy: 0.625
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 2.08 | 0.15 | 25 | 2.0652 | 0.125 |
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+ | 2.057 | 0.31 | 50 | 2.0288 | 0.2083 |
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+ | 2.0031 | 0.46 | 75 | 2.0556 | 0.1667 |
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+ | 1.958 | 0.62 | 100 | 1.9128 | 0.2222 |
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+ | 1.726 | 0.77 | 125 | 1.7048 | 0.3681 |
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+ | 1.6563 | 0.93 | 150 | 1.6522 | 0.3542 |
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+ | 1.7092 | 1.08 | 175 | 1.7439 | 0.2986 |
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+ | 1.5645 | 1.23 | 200 | 1.5394 | 0.4236 |
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+ | 1.4945 | 1.39 | 225 | 1.3462 | 0.5069 |
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+ | 1.4193 | 1.54 | 250 | 1.3745 | 0.4514 |
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+ | 1.3488 | 1.7 | 275 | 1.2707 | 0.5208 |
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+ | 1.3205 | 1.85 | 300 | 1.3819 | 0.5278 |
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+ | 1.2814 | 2.01 | 325 | 1.2694 | 0.5556 |
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+ | 1.118 | 2.16 | 350 | 1.1216 | 0.5625 |
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+ | 1.0507 | 2.31 | 375 | 1.0795 | 0.6042 |
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+ | 0.9967 | 2.47 | 400 | 1.1243 | 0.5764 |
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+ | 0.9471 | 2.62 | 425 | 1.0740 | 0.6181 |
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+ | 0.8582 | 2.78 | 450 | 1.0422 | 0.5903 |
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+ | 0.9264 | 2.93 | 475 | 1.0178 | 0.625 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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