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dbaggi
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my_awesome_mind_model

Audio Classification
Transformers
PyTorch
hubert
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
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End of training

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  1. README.md +11 -11
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.05309734513274336
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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
@@ -32,8 +32,8 @@ 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 minds14 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.6610
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- - Accuracy: 0.0531
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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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- | No log | 0.8 | 3 | 2.6383 | 0.0973 |
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- | No log | 1.87 | 7 | 2.6505 | 0.0885 |
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- | 2.6314 | 2.93 | 11 | 2.6544 | 0.0796 |
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- | 2.6314 | 4.0 | 15 | 2.6581 | 0.0442 |
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- | 2.6314 | 4.8 | 18 | 2.6602 | 0.0354 |
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- | 2.6229 | 5.87 | 22 | 2.6602 | 0.0442 |
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- | 2.6229 | 6.93 | 26 | 2.6605 | 0.0531 |
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- | 2.6107 | 8.0 | 30 | 2.6610 | 0.0531 |
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.061946902654867256
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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-base](https://huggingface.co/facebook/wav2vec2-base) on the minds14 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.6677
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+ - Accuracy: 0.0619
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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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+ | No log | 0.8 | 3 | 2.6505 | 0.0442 |
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+ | No log | 1.87 | 7 | 2.6501 | 0.0885 |
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+ | 2.6323 | 2.93 | 11 | 2.6624 | 0.0796 |
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+ | 2.6323 | 4.0 | 15 | 2.6582 | 0.0796 |
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+ | 2.6323 | 4.8 | 18 | 2.6679 | 0.0796 |
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+ | 2.6214 | 5.87 | 22 | 2.6703 | 0.0619 |
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+ | 2.6214 | 6.93 | 26 | 2.6689 | 0.0619 |
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+ | 2.6175 | 8.0 | 30 | 2.6677 | 0.0619 |
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  ### Framework versions
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