metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: ModernBERT-large-profanity-mr
results: []
ModernBERT-large-profanity-mr
This model is a fine-tuned version of answerdotai/ModernBERT-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
- Accuracy: 1.0
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
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: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Use adamw_hf with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.6922 | 1.0 | 31 | 0.3749 | 0.8819 | 0.4410 | 0.5 | 0.4686 |
| 0.6034 | 2.0 | 62 | 0.3849 | 0.8819 | 0.4410 | 0.5 | 0.4686 |
| 0.4476 | 3.0 | 93 | 0.4496 | 0.8072 | 0.6147 | 0.6698 | 0.6305 |
| 0.2277 | 4.0 | 124 | 0.3633 | 0.8699 | 0.6384 | 0.5639 | 0.5788 |
| 0.0546 | 5.0 | 155 | 0.6659 | 0.8819 | 0.6947 | 0.5354 | 0.5385 |
| 0.0066 | 6.0 | 186 | 0.9790 | 0.8843 | 0.7195 | 0.5544 | 0.5688 |
| 0.0003 | 7.0 | 217 | 1.1011 | 0.8867 | 0.7584 | 0.5469 | 0.5573 |
| 0.0001 | 8.0 | 248 | 1.0485 | 0.8867 | 0.7469 | 0.5558 | 0.5712 |
| 0.0 | 9.0 | 279 | 1.0500 | 0.8867 | 0.7469 | 0.5558 | 0.5712 |
| 0.0 | 9.6885 | 300 | 1.0516 | 0.8867 | 0.7469 | 0.5558 | 0.5712 |
Framework versions
- Transformers 4.48.2
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0