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--- |
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license: mit |
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base_model: roberta-base |
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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: roberta-finetuned-gesture-prediction-21-classes |
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results: [] |
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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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should probably proofread and complete it, then remove this comment. --> |
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# roberta-finetuned-gesture-prediction-21-classes |
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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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More information needed |
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## Intended uses & limitations |
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More information needed |
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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: 4.9033776462709114e-05 |
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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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- num_epochs: 10 |
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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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| 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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