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roberta-finetuned-gesture-prediction-21-classes

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  1. README.md +16 -16
  2. model.safetensors +1 -1
  3. runs/May07_18-40-55_7570e4083a5e/events.out.tfevents.1715107260.7570e4083a5e.601.8 +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 [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.0301
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- - Precision: 0.8177
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- - Recall: 0.8177
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- - F1: 0.8177
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- - Accuracy: 0.8089
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  ## Model description
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@@ -55,21 +55,21 @@ 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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- | 1.8808 | 1.0 | 104 | 1.0755 | 0.7554 | 0.7554 | 0.7554 | 0.7327 |
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- | 0.8843 | 2.0 | 208 | 0.8376 | 0.7637 | 0.7637 | 0.7637 | 0.7465 |
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- | 0.5881 | 3.0 | 312 | 0.7300 | 0.8152 | 0.8152 | 0.8152 | 0.8014 |
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- | 0.4017 | 4.0 | 416 | 0.8043 | 0.7985 | 0.7985 | 0.7985 | 0.7881 |
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- | 0.2652 | 5.0 | 520 | 0.8595 | 0.8118 | 0.8118 | 0.8118 | 0.8018 |
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- | 0.1776 | 6.0 | 624 | 0.9623 | 0.8133 | 0.8133 | 0.8133 | 0.8041 |
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- | 0.1234 | 7.0 | 728 | 0.9631 | 0.8068 | 0.8068 | 0.8068 | 0.7989 |
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- | 0.0829 | 8.0 | 832 | 1.0190 | 0.8256 | 0.8256 | 0.8256 | 0.8168 |
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- | 0.0552 | 9.0 | 936 | 1.0117 | 0.8222 | 0.8222 | 0.8222 | 0.8139 |
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- | 0.0409 | 10.0 | 1040 | 1.0301 | 0.8177 | 0.8177 | 0.8177 | 0.8089 |
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  ### Framework versions
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  - Transformers 4.40.1
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  - Pytorch 2.2.1+cu121
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- - Datasets 2.19.0
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  - Tokenizers 0.19.1
 
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  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.0350
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+ - Precision: 0.8324
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+ - Recall: 0.8324
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+ - F1: 0.8324
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+ - Accuracy: 0.8230
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 1.8808 | 1.0 | 104 | 1.1258 | 0.7513 | 0.7513 | 0.7513 | 0.7258 |
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+ | 0.8843 | 2.0 | 208 | 0.9338 | 0.7765 | 0.7765 | 0.7765 | 0.7578 |
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+ | 0.5881 | 3.0 | 312 | 0.8124 | 0.8173 | 0.8173 | 0.8173 | 0.8011 |
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+ | 0.4017 | 4.0 | 416 | 0.8831 | 0.7973 | 0.7973 | 0.7973 | 0.7848 |
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+ | 0.2652 | 5.0 | 520 | 0.9254 | 0.8300 | 0.8300 | 0.8300 | 0.8172 |
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+ | 0.1776 | 6.0 | 624 | 0.9221 | 0.8310 | 0.8310 | 0.8310 | 0.8180 |
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+ | 0.1234 | 7.0 | 728 | 1.0063 | 0.8211 | 0.8211 | 0.8211 | 0.8112 |
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+ | 0.0829 | 8.0 | 832 | 1.0132 | 0.8298 | 0.8298 | 0.8298 | 0.8201 |
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+ | 0.0552 | 9.0 | 936 | 1.0408 | 0.8290 | 0.8290 | 0.8290 | 0.8189 |
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+ | 0.0409 | 10.0 | 1040 | 1.0350 | 0.8324 | 0.8324 | 0.8324 | 0.8230 |
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  ### Framework versions
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  - Transformers 4.40.1
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  - Pytorch 2.2.1+cu121
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+ - Datasets 2.19.1
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  - Tokenizers 0.19.1
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