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license: apache-2.0
widget:
- text: I'm fine. Who is this?
- text: You can't take anything seriously.
- text: In the end he's going to croak, isn't he?
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-gest-pred-seqeval-partialmatch
results: []
datasets:
- Jsevisal/gesture_pred
pipeline_tag: token-classification
---
<!-- 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. -->
# bert-gest-pred-seqeval-partialmatch
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7270
- Precision: 0.771293
- Recall: 0.720130
- F1: 0.727670
- Accuracy: 0.819896
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- 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 | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.8976 | 1.0 | 147 | 1.1361 | 0.4802 | 0.4141 | 0.4034 | 0.7009 |
| 0.916 | 2.0 | 294 | 0.8206 | 0.6045 | 0.5622 | 0.5493 | 0.7744 |
| 0.5893 | 3.0 | 441 | 0.7711 | 0.7318 | 0.6613 | 0.6747 | 0.7952 |
| 0.4019 | 4.0 | 588 | 0.7270 | 0.7713 | 0.7201 | 0.7277 | 0.8199 |
| 0.2713 | 5.0 | 735 | 0.7353 | 0.8000 | 0.7512 | 0.7545 | 0.8349 |
| 0.1831 | 6.0 | 882 | 0.7802 | 0.7958 | 0.7245 | 0.7375 | 0.8303 |
| 0.1343 | 7.0 | 1029 | 0.7785 | 0.7652 | 0.7351 | 0.7204 | 0.8362 |
| 0.0989 | 8.0 | 1176 | 0.8017 | 0.7753 | 0.7317 | 0.7313 | 0.8322 |
| 0.079 | 9.0 | 1323 | 0.8281 | 0.7844 | 0.7297 | 0.7325 | 0.8349 |
| 0.0673 | 10.0 | 1470 | 0.8238 | 0.7765 | 0.7347 | 0.7289 | 0.8355 |
### Framework versions
- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2 |