metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
- precision
- recall
model-index:
- name: fluency-scorer
results: []
fluency-scorer
This model is a fine-tuned version of answerdotai/ModernBERT-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1451
- F1: 0.9457
- Accuracy: 0.9488
- Precision: 0.9456
- Recall: 0.9488
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: 3e-05
- train_batch_size: 128
- eval_batch_size: 128
- 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: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 0 | 0 | 0.7816 | 0.5684 | 0.4673 | 0.7714 | 0.4673 |
| 0.1379 | 1.0 | 168 | 0.1523 | 0.9426 | 0.9467 | 0.9432 | 0.9467 |
| 0.1464 | 2.0 | 336 | 0.1449 | 0.9458 | 0.9488 | 0.9456 | 0.9488 |
| 0.1592 | 3.0 | 504 | 0.1451 | 0.9457 | 0.9488 | 0.9456 | 0.9488 |
Framework versions
- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0