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distilbert-finetuned-gesture-prediction-21-classes

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  1. README.md +16 -16
  2. model.safetensors +1 -1
  3. runs/May04_10-55-01_19b9be41010d/events.out.tfevents.1714820104.19b9be41010d.571.2 +2 -2
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.9438
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- - Precision: 0.7910
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- - Recall: 0.7910
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- - F1: 0.7910
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- - Accuracy: 0.7817
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 6.042200829392303e-05
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  - train_batch_size: 64
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  - eval_batch_size: 64
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  - seed: 42
@@ -55,16 +55,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 2.4003 | 1.0 | 26 | 1.4948 | 0.6512 | 0.6512 | 0.6512 | 0.6206 |
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- | 1.2197 | 2.0 | 52 | 1.0008 | 0.7501 | 0.7501 | 0.7501 | 0.7356 |
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- | 0.81 | 3.0 | 78 | 0.8907 | 0.7696 | 0.7696 | 0.7696 | 0.7555 |
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- | 0.5619 | 4.0 | 104 | 0.9091 | 0.7628 | 0.7628 | 0.7628 | 0.7495 |
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- | 0.3944 | 5.0 | 130 | 0.8791 | 0.7853 | 0.7853 | 0.7853 | 0.7749 |
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- | 0.2907 | 6.0 | 156 | 0.8973 | 0.7845 | 0.7845 | 0.7845 | 0.7733 |
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- | 0.2214 | 7.0 | 182 | 0.9209 | 0.7874 | 0.7874 | 0.7874 | 0.7779 |
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- | 0.1722 | 8.0 | 208 | 0.9446 | 0.7878 | 0.7878 | 0.7878 | 0.7787 |
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- | 0.1454 | 9.0 | 234 | 0.9406 | 0.7882 | 0.7882 | 0.7882 | 0.7789 |
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- | 0.128 | 10.0 | 260 | 0.9438 | 0.7910 | 0.7910 | 0.7910 | 0.7817 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.2008
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+ - Precision: 0.7823
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+ - Recall: 0.7823
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+ - F1: 0.7823
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+ - Accuracy: 0.7745
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 9.96098704459956e-05
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  - train_batch_size: 64
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  - eval_batch_size: 64
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.4985 | 1.0 | 26 | 1.0570 | 0.7288 | 0.7288 | 0.7288 | 0.7177 |
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+ | 0.2387 | 2.0 | 52 | 1.0720 | 0.7775 | 0.7775 | 0.7775 | 0.7672 |
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+ | 0.1348 | 3.0 | 78 | 1.0681 | 0.7775 | 0.7775 | 0.7775 | 0.7682 |
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+ | 0.0811 | 4.0 | 104 | 1.1143 | 0.7884 | 0.7884 | 0.7884 | 0.7781 |
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+ | 0.0565 | 5.0 | 130 | 1.1128 | 0.7867 | 0.7867 | 0.7867 | 0.7783 |
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+ | 0.0419 | 6.0 | 156 | 1.1051 | 0.7966 | 0.7966 | 0.7966 | 0.7880 |
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+ | 0.0257 | 7.0 | 182 | 1.1567 | 0.7839 | 0.7839 | 0.7839 | 0.7737 |
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+ | 0.0217 | 8.0 | 208 | 1.1675 | 0.7859 | 0.7859 | 0.7859 | 0.7757 |
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+ | 0.0145 | 9.0 | 234 | 1.1976 | 0.7847 | 0.7847 | 0.7847 | 0.7769 |
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+ | 0.0115 | 10.0 | 260 | 1.2008 | 0.7823 | 0.7823 | 0.7823 | 0.7745 |
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  ### Framework versions
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