metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ModernBERT-base-zeroshot-v2.0-2024-12-28-09-01
results: []
ModernBERT-base-zeroshot-v2.0-2024-12-28-09-01
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: 0.1856
- F1 Macro: 0.6373
- F1 Micro: 0.7076
- Accuracy Balanced: 0.6761
- Accuracy: 0.7076
- Precision Macro: 0.6700
- Recall Macro: 0.6761
- Precision Micro: 0.7076
- Recall Micro: 0.7076
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
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.2321 | 1.0 | 33915 | 0.3726 | 0.8316 | 0.8458 | 0.8332 | 0.8458 | 0.8301 | 0.8332 | 0.8458 | 0.8458 |
| 0.1305 | 2.0 | 67830 | 0.4350 | 0.8396 | 0.8541 | 0.8389 | 0.8541 | 0.8403 | 0.8389 | 0.8541 | 0.8541 |
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0