---
library_name: transformers
license: apache-2.0
base_model: Geotrend/bert-base-th-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bert-base-th-cased-intent-booking
  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. -->

# bert-base-th-cased-intent-booking

This model is a fine-tuned version of [Geotrend/bert-base-th-cased](https://huggingface.co/Geotrend/bert-base-th-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2346
- Accuracy: 0.9369
- F1: 0.9340
- Precision: 0.9471
- Recall: 0.9369

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 64
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.9427        | 1.0   | 65   | 0.7129          | 0.8964   | 0.8947 | 0.9055    | 0.8964 |
| 0.48          | 2.0   | 130  | 0.2325          | 0.9369   | 0.9365 | 0.9390    | 0.9369 |
| 0.1783        | 3.0   | 195  | 0.2001          | 0.9505   | 0.9511 | 0.9578    | 0.9505 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1