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---
license: apache-2.0
tags:
- generated_from_trainer
datasets: qfrodicio/gesture-prediction-9-classes
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: distilbert-finetuned-gesture-prediction-9-classes
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-finetuned-gesture-prediction-9-classes
This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset.
It achieves the following results on the validation set:
- Loss: 0.6479
- Accuracy: 0.8214
- Precision: 0.8230
- Recall: 0.8214
- F1: 0.8172
It achieves the following results on the test set:
- Loss: 0.6475
- Accuracy: 0.8144
- Precision: 0.8144
- Recall: 0.8144
- F1: 0.8095
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
The model has been trained on the qfrodicio/gesture-prediction-9-classes dataset
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- weight_decay: 0.01
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.6636 | 1.0 | 87 | 0.9715 | 0.7270 | 0.6909 | 0.7270 | 0.6897 |
| 0.7503 | 2.0 | 174 | 0.7360 | 0.7987 | 0.7874 | 0.7987 | 0.7879 |
| 0.5283 | 3.0 | 261 | 0.6831 | 0.8056 | 0.8046 | 0.8056 | 0.8005 |
| 0.3853 | 4.0 | 348 | 0.6479 | 0.8214 | 0.8230 | 0.8214 | 0.8172 |
| 0.28 | 5.0 | 435 | 0.6570 | 0.8314 | 0.8348 | 0.8314 | 0.8289 |
| 0.2163 | 6.0 | 522 | 0.6887 | 0.8322 | 0.8346 | 0.8322 | 0.8298 |
| 0.158 | 7.0 | 609 | 0.7078 | 0.8336 | 0.8362 | 0.8336 | 0.8311 |
| 0.1308 | 8.0 | 696 | 0.7197 | 0.8415 | 0.8444 | 0.8415 | 0.8394 |
| 0.1061 | 9.0 | 783 | 0.7362 | 0.8419 | 0.8441 | 0.8419 | 0.8394 |
| 0.0947 | 10.0 | 870 | 0.7412 | 0.8435 | 0.8458 | 0.8435 | 0.8410 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
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