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DanielDBGC
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my_awesome_lang_class_mind_model

Audio Classification
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Model card Files
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 Metrics Community
DanielDBGC commited on
Commit
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1 Parent(s): 471bc86

End of training

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Files changed (3) hide show
  1. README.md +13 -13
  2. model.safetensors +1 -1
  3. runs/Dec08_18-37-18_Bingus/events.out.tfevents.1702082241.Bingus.7224.0 +2 -2
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: 0.193390452876377
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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: 2.3379
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- - Accuracy: 0.1934
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  ## Model description
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@@ -67,16 +67,16 @@ 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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- | 2.5909 | 1.0 | 51 | 2.5758 | 0.1414 |
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- | 2.4339 | 1.99 | 102 | 2.4560 | 0.1487 |
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- | 2.3971 | 2.99 | 153 | 2.4255 | 0.1634 |
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- | 2.3711 | 4.0 | 205 | 2.4043 | 0.1714 |
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- | 2.3746 | 5.0 | 256 | 2.3757 | 0.1738 |
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- | 2.3046 | 5.99 | 307 | 2.3663 | 0.1879 |
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- | 2.2725 | 6.99 | 358 | 2.3563 | 0.1916 |
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- | 2.2593 | 8.0 | 410 | 2.3480 | 0.1922 |
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- | 2.2463 | 9.0 | 461 | 2.3408 | 0.1946 |
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- | 2.2278 | 9.95 | 510 | 2.3379 | 0.1934 |
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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: 0.21236230110159118
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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: 2.3072
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+ - Accuracy: 0.2124
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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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+ | 2.597 | 1.0 | 51 | 2.5777 | 0.1481 |
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+ | 2.4608 | 1.99 | 102 | 2.4484 | 0.1567 |
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+ | 2.4352 | 2.99 | 153 | 2.4153 | 0.1548 |
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+ | 2.3965 | 4.0 | 205 | 2.3796 | 0.1897 |
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+ | 2.363 | 5.0 | 256 | 2.3622 | 0.1922 |
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+ | 2.3369 | 5.99 | 307 | 2.3496 | 0.1854 |
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+ | 2.292 | 6.99 | 358 | 2.3286 | 0.2038 |
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+ | 2.2788 | 8.0 | 410 | 2.3170 | 0.2075 |
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+ | 2.2537 | 9.0 | 461 | 2.3090 | 0.2044 |
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+ | 2.241 | 9.95 | 510 | 2.3072 | 0.2124 |
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  ### Framework versions
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