---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: intent-finetuned-intent-detection
  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-finetuned-intent-detection

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6938
- Accuracy: 0.8638
- F1: 0.8593

## 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: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 3.0316        | 1.0   | 180  | 1.7788          | 0.6819   | 0.6352 |
| 1.4515        | 2.0   | 360  | 1.0539          | 0.7956   | 0.7735 |
| 0.9212        | 3.0   | 540  | 0.8143          | 0.8457   | 0.8382 |
| 0.6883        | 4.0   | 720  | 0.7246          | 0.8601   | 0.8544 |
| 0.583         | 5.0   | 900  | 0.6938          | 0.8638   | 0.8593 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2