metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ModernBERT-large-zeroshot-v2.0-2024-12-28-00-13
results: []
ModernBERT-large-zeroshot-v2.0-2024-12-28-00-13
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: 0.1803
- F1 Macro: 0.6624
- F1 Micro: 0.7304
- Accuracy Balanced: 0.6979
- Accuracy: 0.7304
- Precision Macro: 0.6899
- Recall Macro: 0.6979
- Precision Micro: 0.7304
- Recall Micro: 0.7304
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: 9e-06
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | Accuracy Balanced | Accuracy | Precision Macro | Recall Macro | Precision Micro | Recall Micro |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.3865 | 1.0 | 33915 | 0.3321 | 0.8584 | 0.8704 | 0.8600 | 0.8704 | 0.8569 | 0.8600 | 0.8704 | 0.8704 |
| 0.2456 | 2.0000 | 67828 | 0.4069 | 0.8600 | 0.8728 | 0.8590 | 0.8728 | 0.8610 | 0.8590 | 0.8728 | 0.8728 |
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0