metadata
library_name: transformers
base_model: AnhNam/Luong_modernBert_ft
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: LTER_goc_modernBert_ft
results: []
LTER_goc_modernBert_ft
This model is a fine-tuned version of AnhNam/Luong_modernBert_ft on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4084
- F1: 0.8571
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-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.1646 | 1.0 | 14 | 0.5255 | 0.5578 |
| 0.1971 | 2.0 | 28 | 0.4755 | 0.7016 |
| 0.1588 | 3.0 | 42 | 0.4503 | 0.7823 |
| 0.0806 | 4.0 | 56 | 0.4234 | 0.8571 |
| 0.0221 | 5.0 | 70 | 0.4139 | 0.8571 |
| 0.0196 | 6.0 | 84 | 0.4086 | 0.8571 |
| 0.2718 | 6.5185 | 91 | 0.4084 | 0.8571 |
Framework versions
- Transformers 4.48.2
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0