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library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: results
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# results
This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2000
- Accuracy: 0.9433
- F1: 0.9429
- Precision: 0.9508
- Recall: 0.9433
## 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: 4e-05
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 12
- 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: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 3.8028 | 0.0833 | 25 | 1.5191 | 0.3944 | 0.2893 | 0.4598 | 0.3944 |
| 2.2046 | 0.1667 | 50 | 0.7147 | 0.75 | 0.7423 | 0.7685 | 0.75 |
| 1.2172 | 0.25 | 75 | 0.6074 | 0.7989 | 0.7727 | 0.8508 | 0.7989 |
| 0.9054 | 0.3333 | 100 | 0.3817 | 0.8656 | 0.8637 | 0.8907 | 0.8656 |
| 0.873 | 0.4167 | 125 | 0.3460 | 0.8678 | 0.8665 | 0.8810 | 0.8678 |
| 0.7074 | 0.5 | 150 | 0.2918 | 0.8889 | 0.8848 | 0.9159 | 0.8889 |
| 1.0552 | 0.5833 | 175 | 0.2550 | 0.89 | 0.8868 | 0.9130 | 0.89 |
| 0.5167 | 0.6667 | 200 | 0.2660 | 0.9044 | 0.9043 | 0.9071 | 0.9044 |
| 0.3174 | 0.75 | 225 | 0.2641 | 0.8956 | 0.8882 | 0.9235 | 0.8956 |
| 0.3369 | 0.8333 | 250 | 0.1745 | 0.9489 | 0.9490 | 0.9520 | 0.9489 |
| 0.2966 | 0.9167 | 275 | 0.1484 | 0.9567 | 0.9568 | 0.9589 | 0.9567 |
| 0.5544 | 1.0 | 300 | 0.2000 | 0.9433 | 0.9429 | 0.9508 | 0.9433 |
### Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
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