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---
license: apache-2.0
base_model: google-bert/bert-large-cased-whole-word-masking
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: Intent-classification-BERT-Large-Ashuv5
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. -->
# Intent-classification-BERT-Large-Ashuv5
This model is a fine-tuned version of [google-bert/bert-large-cased-whole-word-masking](https://huggingface.co./google-bert/bert-large-cased-whole-word-masking) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7988
- Accuracy: 0.1420
- F1: 0.0414
- Precision: 0.0237
- Recall: 0.1667
## 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: 0.0005
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 2.1123 | 0.24 | 10 | 1.8066 | 0.2174 | 0.0595 | 0.0362 | 0.1667 |
| 1.8577 | 0.49 | 20 | 1.9500 | 0.1242 | 0.0368 | 0.0207 | 0.1667 |
| 1.8864 | 0.73 | 30 | 1.7999 | 0.1801 | 0.0509 | 0.0300 | 0.1667 |
| 1.8516 | 0.98 | 40 | 1.8570 | 0.1429 | 0.0417 | 0.0238 | 0.1667 |
| 1.8664 | 1.22 | 50 | 1.8667 | 0.1242 | 0.0368 | 0.0207 | 0.1667 |
| 1.8207 | 1.46 | 60 | 1.9616 | 0.1180 | 0.0352 | 0.0197 | 0.1667 |
| 1.8652 | 1.71 | 70 | 1.7831 | 0.2174 | 0.0595 | 0.0362 | 0.1667 |
| 1.8372 | 1.95 | 80 | 1.8018 | 0.2174 | 0.0595 | 0.0362 | 0.1667 |
| 1.8671 | 2.2 | 90 | 1.8436 | 0.1180 | 0.0352 | 0.0197 | 0.1667 |
| 1.8484 | 2.44 | 100 | 1.7722 | 0.2174 | 0.0595 | 0.0362 | 0.1667 |
| 1.8262 | 2.68 | 110 | 1.7752 | 0.2174 | 0.0595 | 0.0362 | 0.1667 |
| 1.8292 | 2.93 | 120 | 1.8064 | 0.1242 | 0.0368 | 0.0207 | 0.1667 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2
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