ekunish commited on
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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: Accuracy
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  type: accuracy
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- value: 0.04424778761061947
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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
@@ -33,8 +33,8 @@ 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: 2.6651
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- - Accuracy: 0.0442
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  ## Model description
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@@ -68,16 +68,16 @@ 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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- | No log | 0.8 | 3 | 2.6346 | 0.0531 |
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- | No log | 1.8 | 6 | 2.6432 | 0.0531 |
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- | No log | 2.8 | 9 | 2.6469 | 0.0619 |
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- | 3.0292 | 3.8 | 12 | 2.6467 | 0.0531 |
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- | 3.0292 | 4.8 | 15 | 2.6552 | 0.0619 |
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- | 3.0292 | 5.8 | 18 | 2.6546 | 0.0531 |
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- | 3.0163 | 6.8 | 21 | 2.6559 | 0.0619 |
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- | 3.0163 | 7.8 | 24 | 2.6609 | 0.0531 |
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- | 3.0163 | 8.8 | 27 | 2.6644 | 0.0442 |
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- | 3.0031 | 9.8 | 30 | 2.6651 | 0.0442 |
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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: 0.09734513274336283
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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: 2.6487
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+ - Accuracy: 0.0973
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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 | 2.6373 | 0.0796 |
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+ | No log | 1.8 | 6 | 2.6331 | 0.0973 |
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+ | No log | 2.8 | 9 | 2.6393 | 0.0796 |
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+ | 3.0295 | 3.8 | 12 | 2.6450 | 0.0796 |
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+ | 3.0295 | 4.8 | 15 | 2.6475 | 0.0885 |
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+ | 3.0295 | 5.8 | 18 | 2.6493 | 0.0796 |
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+ | 3.0135 | 6.8 | 21 | 2.6494 | 0.0885 |
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+ | 3.0135 | 7.8 | 24 | 2.6501 | 0.0973 |
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+ | 3.0135 | 8.8 | 27 | 2.6489 | 0.0973 |
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+ | 3.0007 | 9.8 | 30 | 2.6487 | 0.0973 |
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  ### Framework versions
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