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cotysong113
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my_awesome_mind_model

Audio Classification
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Model card Files
xet
Metrics Community
cotysong113 commited on
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End of training

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Files changed (3) hide show
  1. README.md +18 -17
  2. runs/Dec09_16-54-48_bogon/events.out.tfevents.1733734490.bogon.89513.3 +2 -2
  3. runs/Dec09_16-55-15_bogon/events.out.tfevents.1733734516.bogon.89513.4 +2 -2
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: 0.07964601769911504
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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: 2.6599
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- - Accuracy: 0.0796
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  ## Model description
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@@ -66,22 +66,23 @@ The following hyperparameters were used during training:
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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 | 0.8 | 3 | 2.6397 | 0.0531 |
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- | No log | 1.9333 | 7 | 2.6456 | 0.0796 |
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- | 2.6345 | 2.8 | 10 | 2.6545 | 0.0531 |
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- | 2.6345 | 3.9333 | 14 | 2.6604 | 0.0531 |
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- | 2.6345 | 4.8 | 17 | 2.6609 | 0.0531 |
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- | 2.62 | 5.9333 | 21 | 2.6603 | 0.0796 |
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- | 2.62 | 6.8 | 24 | 2.6610 | 0.0796 |
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- | 2.62 | 7.9333 | 28 | 2.6598 | 0.0796 |
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- | 2.6132 | 8.5333 | 30 | 2.6599 | 0.0796 |
 
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  ### Framework versions
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- - Transformers 4.46.2
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- - Pytorch 2.5.1+cu124
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  - Datasets 3.1.0
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- - Tokenizers 0.20.1
 
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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
 
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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: 2.6547
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+ - Accuracy: 0.0531
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  ## Model description
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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 | 0.8 | 3 | 2.6432 | 0.0619 |
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+ | No log | 1.8 | 6 | 2.6425 | 0.0442 |
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+ | No log | 2.8 | 9 | 2.6435 | 0.0531 |
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+ | 3.0271 | 3.8 | 12 | 2.6428 | 0.0531 |
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+ | 3.0271 | 4.8 | 15 | 2.6446 | 0.0531 |
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+ | 3.0271 | 5.8 | 18 | 2.6475 | 0.0531 |
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+ | 3.0086 | 6.8 | 21 | 2.6507 | 0.0531 |
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+ | 3.0086 | 7.8 | 24 | 2.6537 | 0.0531 |
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+ | 3.0086 | 8.8 | 27 | 2.6549 | 0.0531 |
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+ | 3.0005 | 9.8 | 30 | 2.6547 | 0.0531 |
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  ### Framework versions
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+ - Transformers 4.47.0
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+ - Pytorch 2.5.1
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  - Datasets 3.1.0
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+ - Tokenizers 0.21.0
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