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bert-finetuned-gesture-prediction-21-classes

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  1. README.md +29 -37
  2. model.safetensors +1 -1
  3. runs/May04_10-40-06_19b9be41010d/events.out.tfevents.1714819211.19b9be41010d.571.0 +2 -2
README.md CHANGED
@@ -1,13 +1,13 @@
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  ---
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  license: apache-2.0
 
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  tags:
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  - generated_from_trainer
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- datasets: qfrodicio/gesture-prediction-21-classes
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  metrics:
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- - accuracy
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  - precision
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  - recall
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  - f1
 
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  model-index:
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  - name: bert-finetuned-gesture-prediction-21-classes
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  results: []
@@ -18,20 +18,13 @@ should probably proofread and complete it, then remove this comment. -->
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  # bert-finetuned-gesture-prediction-21-classes
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- This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
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- It achieves the following results on the validation set:
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- - Loss: 0.8664
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- - Accuracy: 0.8123
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- - Precision: 0.8122
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- - Recall: 0.8123
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- - F1: 0.8048
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-
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- It achieves the following results on the test set:
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- - Loss: 0.8381
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- - Accuracy: 0.7884
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- - Precision: 0.7954
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- - Recall: 0.7884
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- - F1: 0.7827
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  ## Model description
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@@ -43,17 +36,16 @@ More information needed
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  ## Training and evaluation data
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- The model has been trained with the qfrodicio/gesture-prediction-21-classes dataset
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  ## Training procedure
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 2e-05
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- - weight_decay: 0.01
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- - train_batch_size: 16
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- - eval_batch_size: 16
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | 2.225 | 1.0 | 104 | 1.3314 | 0.7115 | 0.6469 | 0.7115 | 0.6675 |
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- | 1.0881 | 2.0 | 208 | 0.9569 | 0.7750 | 0.7577 | 0.7750 | 0.7525 |
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- | 0.7006 | 3.0 | 312 | 0.8805 | 0.7959 | 0.7917 | 0.7959 | 0.7831 |
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- | 0.4943 | 4.0 | 416 | 0.8664 | 0.8123 | 0.8122 | 0.8123 | 0.8048 |
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- | 0.3372 | 5.0 | 520 | 0.8765 | 0.8130 | 0.8102 | 0.8130 | 0.8053 |
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- | 0.2416 | 6.0 | 624 | 0.8772 | 0.8166 | 0.8139 | 0.8166 | 0.8107 |
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- | 0.178 | 7.0 | 728 | 0.9186 | 0.8217 | 0.8186 | 0.8217 | 0.8167 |
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- | 0.1302 | 8.0 | 832 | 0.9186 | 0.8202 | 0.8183 | 0.8202 | 0.8165 |
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- | 0.1063 | 9.0 | 936 | 0.9618 | 0.8245 | 0.8213 | 0.8245 | 0.8198 |
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- | 0.094 | 10.0 | 1040 | 0.9660 | 0.8214 | 0.8184 | 0.8214 | 0.8166 |
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  ### Framework versions
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- - Transformers 4.26.1
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- - Pytorch 1.13.1+cu116
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- - Datasets 2.10.1
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- - Tokenizers 0.13.2
 
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  ---
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  license: apache-2.0
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+ base_model: bert-base-cased
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  tags:
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  - generated_from_trainer
 
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  metrics:
 
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  - precision
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  - recall
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  - f1
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+ - accuracy
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  model-index:
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  - name: bert-finetuned-gesture-prediction-21-classes
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  results: []
 
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  # bert-finetuned-gesture-prediction-21-classes
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+ This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9626
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+ - Precision: 0.8178
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+ - Recall: 0.8178
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+ - F1: 0.8178
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+ - Accuracy: 0.8075
 
 
 
 
 
 
 
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  ## Model description
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  ## Training and evaluation data
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+ More information needed
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  ## Training procedure
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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
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
 
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 2.3221 | 1.0 | 26 | 1.4762 | 0.6969 | 0.6969 | 0.6969 | 0.6192 |
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+ | 1.2093 | 2.0 | 52 | 0.9843 | 0.7634 | 0.7634 | 0.7634 | 0.7469 |
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+ | 0.7309 | 3.0 | 78 | 0.8908 | 0.7878 | 0.7878 | 0.7878 | 0.7690 |
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+ | 0.4596 | 4.0 | 104 | 0.8613 | 0.7894 | 0.7894 | 0.7894 | 0.7763 |
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+ | 0.2947 | 5.0 | 130 | 0.8971 | 0.8075 | 0.8075 | 0.8075 | 0.7962 |
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+ | 0.1921 | 6.0 | 156 | 0.8838 | 0.8063 | 0.8063 | 0.8063 | 0.7956 |
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+ | 0.1348 | 7.0 | 182 | 0.9271 | 0.8166 | 0.8166 | 0.8166 | 0.8057 |
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+ | 0.0986 | 8.0 | 208 | 0.9548 | 0.8137 | 0.8137 | 0.8137 | 0.8035 |
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+ | 0.073 | 9.0 | 234 | 0.9553 | 0.8174 | 0.8174 | 0.8174 | 0.8063 |
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+ | 0.0619 | 10.0 | 260 | 0.9626 | 0.8178 | 0.8178 | 0.8178 | 0.8075 |
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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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