metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: MBERT-Clinc
results: []
MBERT-Clinc
This model is a fine-tuned version of answerdotai/ModernBERT-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1834
- Accuracy: 0.9681
- F1: 0.9677
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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.5635 | 0.4193 | 200 | 0.4160 | 0.8932 | 0.8911 |
| 0.2762 | 0.8386 | 400 | 0.2421 | 0.9387 | 0.9371 |
| 0.1315 | 1.2579 | 600 | 0.3010 | 0.9390 | 0.9376 |
| 0.0801 | 1.6771 | 800 | 0.2305 | 0.9552 | 0.9547 |
| 0.0736 | 2.0964 | 1000 | 0.2306 | 0.9577 | 0.9573 |
| 0.0288 | 2.5157 | 1200 | 0.2389 | 0.9545 | 0.9532 |
| 0.0159 | 2.9350 | 1400 | 0.1933 | 0.9661 | 0.9656 |
| 0.0069 | 3.3543 | 1600 | 0.1857 | 0.9652 | 0.9648 |
| 0.0062 | 3.7736 | 1800 | 0.1807 | 0.9677 | 0.9674 |
| 0.0061 | 4.1929 | 2000 | 0.1841 | 0.9674 | 0.9671 |
| 0.0011 | 4.6122 | 2200 | 0.1834 | 0.9681 | 0.9677 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1