metadata
library_name: transformers
base_model: airesearch/wangchanberta-base-att-spm-uncased
tags:
- generated_from_trainer
datasets:
- orchid_corpus
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: my_test_model
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: orchid_corpus
type: orchid_corpus
config: thai_orchid_dataset
split: test
args: thai_orchid_dataset
metrics:
- name: Precision
type: precision
value: 0.6866152910160211
- name: Recall
type: recall
value: 0.6612566160817172
- name: F1
type: f1
value: 0.673697406254042
- name: Accuracy
type: accuracy
value: 0.8615229701891011
my_test_model
This model is a fine-tuned version of airesearch/wangchanberta-base-att-spm-uncased on the orchid_corpus dataset. It achieves the following results on the evaluation set:
- Loss: 0.4402
- Precision: 0.6866
- Recall: 0.6613
- F1: 0.6737
- Accuracy: 0.8615
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.6071 | 1.0 | 1157 | 0.4812 | 0.6686 | 0.6451 | 0.6566 | 0.8524 |
| 0.4831 | 2.0 | 2314 | 0.4402 | 0.6866 | 0.6613 | 0.6737 | 0.8615 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0