metadata
license: cc-by-4.0
base_model: pythainlp/thainer-corpus-v2-base-model
tags:
- generated_from_trainer
datasets:
- lst20
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: toneza
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: lst20
type: lst20
config: default
split: validation
args: default
metrics:
- name: Precision
type: precision
value: 0.768370802562324
- name: Recall
type: recall
value: 0.8120041393583994
- name: F1
type: f1
value: 0.7895851240015932
- name: Accuracy
type: accuracy
value: 0.956478116244312
toneza
This model is a fine-tuned version of pythainlp/thainer-corpus-v2-base-model on the lst20 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1293
- Precision: 0.7684
- Recall: 0.8120
- F1: 0.7896
- Accuracy: 0.9565
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: 32
- 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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1226 | 1.0 | 1978 | 0.1416 | 0.7414 | 0.7802 | 0.7603 | 0.9518 |
| 0.098 | 2.0 | 3956 | 0.1324 | 0.7602 | 0.7966 | 0.7780 | 0.9545 |
| 0.0895 | 3.0 | 5934 | 0.1293 | 0.7684 | 0.8120 | 0.7896 | 0.9565 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0