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shevek
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my_awesome_speach_model

Audio Classification
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
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End of training

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  1. README.md +39 -21
  2. model.safetensors +1 -1
  3. runs/Dec15_07-07-20_4a551e90a1ca/events.out.tfevents.1734246441.4a551e90a1ca.2138.5 +2 -2
README.md CHANGED
@@ -18,8 +18,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.9803
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- - Accuracy: 0.6923
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  ## Model description
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@@ -47,30 +47,48 @@ The following hyperparameters were used during training:
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 20
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-------:|:----:|:---------------:|:--------:|
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- | No log | 0.8889 | 6 | 0.8543 | 0.4615 |
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- | 0.3921 | 1.9259 | 13 | 1.0292 | 0.3846 |
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- | 0.4899 | 2.9630 | 20 | 0.7720 | 0.6923 |
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- | 0.4899 | 4.0 | 27 | 0.6074 | 0.6923 |
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- | 0.4529 | 4.8889 | 33 | 0.7270 | 0.6923 |
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- | 0.3684 | 5.9259 | 40 | 0.6883 | 0.6923 |
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- | 0.3684 | 6.9630 | 47 | 0.8489 | 0.6154 |
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- | 0.2618 | 8.0 | 54 | 0.8669 | 0.6154 |
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- | 0.2343 | 8.8889 | 60 | 0.9146 | 0.6923 |
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- | 0.2343 | 9.9259 | 67 | 0.8657 | 0.6154 |
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- | 0.2193 | 10.9630 | 74 | 0.6177 | 0.7692 |
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- | 0.2718 | 12.0 | 81 | 0.9329 | 0.5385 |
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- | 0.2718 | 12.8889 | 87 | 1.3075 | 0.5385 |
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- | 0.2549 | 13.9259 | 94 | 0.5816 | 0.8462 |
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- | 0.1191 | 14.9630 | 101 | 0.6591 | 0.7692 |
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- | 0.1191 | 16.0 | 108 | 0.7349 | 0.7692 |
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- | 0.1449 | 16.8889 | 114 | 0.9123 | 0.6923 |
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- | 0.0914 | 17.7778 | 120 | 0.9803 | 0.6923 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8215
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+ - Accuracy: 0.6154
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  ## Model description
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 40
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-------:|:----:|:---------------:|:--------:|
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+ | No log | 0.8889 | 6 | 0.6905 | 0.6923 |
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+ | 0.6936 | 1.9259 | 13 | 0.7083 | 0.3077 |
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+ | 0.6859 | 2.9630 | 20 | 0.7061 | 0.3846 |
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+ | 0.6859 | 4.0 | 27 | 0.7065 | 0.4615 |
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+ | 0.6738 | 4.8889 | 33 | 0.7058 | 0.5385 |
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+ | 0.6487 | 5.9259 | 40 | 0.7190 | 0.5385 |
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+ | 0.6487 | 6.9630 | 47 | 0.6488 | 0.6154 |
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+ | 0.5804 | 8.0 | 54 | 0.6696 | 0.6154 |
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+ | 0.6227 | 8.8889 | 60 | 0.7988 | 0.3846 |
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+ | 0.6227 | 9.9259 | 67 | 0.6253 | 0.6923 |
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+ | 0.6318 | 10.9630 | 74 | 0.6760 | 0.6154 |
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+ | 0.6617 | 12.0 | 81 | 0.9642 | 0.3077 |
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+ | 0.6617 | 12.8889 | 87 | 0.7761 | 0.5385 |
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+ | 0.6052 | 13.9259 | 94 | 0.8490 | 0.4615 |
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+ | 0.5238 | 14.9630 | 101 | 0.7963 | 0.4615 |
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+ | 0.5238 | 16.0 | 108 | 0.7485 | 0.5385 |
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+ | 0.452 | 16.8889 | 114 | 0.7720 | 0.5385 |
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+ | 0.3813 | 17.9259 | 121 | 0.7478 | 0.6154 |
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+ | 0.3813 | 18.9630 | 128 | 0.8406 | 0.6154 |
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+ | 0.4809 | 20.0 | 135 | 0.6624 | 0.6923 |
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+ | 0.3698 | 20.8889 | 141 | 0.7520 | 0.6154 |
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+ | 0.3698 | 21.9259 | 148 | 0.8275 | 0.5385 |
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+ | 0.2959 | 22.9630 | 155 | 0.8472 | 0.5385 |
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+ | 0.3976 | 24.0 | 162 | 1.0899 | 0.4615 |
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+ | 0.3976 | 24.8889 | 168 | 0.8758 | 0.5385 |
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+ | 0.3788 | 25.9259 | 175 | 0.5872 | 0.7692 |
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+ | 0.3511 | 26.9630 | 182 | 0.7996 | 0.6154 |
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+ | 0.3511 | 28.0 | 189 | 0.7726 | 0.6154 |
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+ | 0.2797 | 28.8889 | 195 | 0.7310 | 0.6923 |
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+ | 0.2445 | 29.9259 | 202 | 0.7223 | 0.6154 |
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+ | 0.2445 | 30.9630 | 209 | 0.7139 | 0.6923 |
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+ | 0.2299 | 32.0 | 216 | 0.7540 | 0.6923 |
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+ | 0.2101 | 32.8889 | 222 | 0.7878 | 0.6154 |
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+ | 0.2101 | 33.9259 | 229 | 0.7942 | 0.6154 |
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+ | 0.2043 | 34.9630 | 236 | 0.8193 | 0.6154 |
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+ | 0.1638 | 35.5556 | 240 | 0.8215 | 0.6154 |
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  ### Framework versions
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