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--- |
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license: apache-2.0 |
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base_model: distilbert-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: distilbert-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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# distilbert-finetuned-gesture-prediction-21-classes |
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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: 1.0324 |
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- Precision: 0.8139 |
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- Recall: 0.8139 |
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- F1: 0.8139 |
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- Accuracy: 0.8022 |
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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: 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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- 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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| 2.1035 | 1.0 | 26 | 1.2829 | 0.7042 | 0.7042 | 0.7042 | 0.6806 | |
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| 0.9959 | 2.0 | 52 | 0.9482 | 0.7756 | 0.7756 | 0.7756 | 0.7621 | |
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| 0.6164 | 3.0 | 78 | 0.8716 | 0.7849 | 0.7849 | 0.7849 | 0.7685 | |
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| 0.3812 | 4.0 | 104 | 0.8710 | 0.8004 | 0.8004 | 0.8004 | 0.7867 | |
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| 0.2325 | 5.0 | 130 | 0.9558 | 0.7916 | 0.7916 | 0.7916 | 0.7788 | |
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| 0.1558 | 6.0 | 156 | 0.9310 | 0.8077 | 0.8077 | 0.8077 | 0.7949 | |
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| 0.0983 | 7.0 | 182 | 0.9989 | 0.8121 | 0.8121 | 0.8121 | 0.7992 | |
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| 0.0697 | 8.0 | 208 | 1.0241 | 0.8083 | 0.8083 | 0.8083 | 0.7963 | |
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| 0.05 | 9.0 | 234 | 1.0352 | 0.8110 | 0.8110 | 0.8110 | 0.7991 | |
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| 0.0403 | 10.0 | 260 | 1.0324 | 0.8139 | 0.8139 | 0.8139 | 0.8022 | |
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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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