---
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