---
base_model: airesearch/wangchanberta-base-att-spm-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: lst20-sent-segment
  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. -->

# lst20-sent-segment

This model is a fine-tuned version of [airesearch/wangchanberta-base-att-spm-uncased](https://huggingface.co/airesearch/wangchanberta-base-att-spm-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1513
- Precision: 0.7125
- Recall: 0.5426
- F1: 0.6160
- Accuracy: 0.9403

## 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: 1e-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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1842        | 1.0   | 1274 | 0.1596          | 0.6990    | 0.4995 | 0.5827 | 0.9361   |
| 0.1622        | 2.0   | 2548 | 0.1513          | 0.7052    | 0.5330 | 0.6071 | 0.9389   |
| 0.1554        | 3.0   | 3822 | 0.1513          | 0.7125    | 0.5426 | 0.6160 | 0.9403   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0