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: 0.5555
- F1: 0.6007
- Accuracy: 0.696
- Precision: 0.6271
- Recall: 0.696
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 | 0.8275 | 0.2749 | 0.336 | 0.5265 | 0.336 |
| No log | 1.0 | 8 | 0.6056 | 0.6355 | 0.669 | 0.6265 | 0.669 |
| 0.7136 | 2.0 | 16 | 0.5566 | 0.6004 | 0.693 | 0.6178 | 0.693 |
| 0.5579 | 3.0 | 24 | 0.5555 | 0.6007 | 0.696 | 0.6271 | 0.696 |
Framework versions
- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0