metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: results_bert
results: []
results_bert
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: 0.4209
- Accuracy: 0.8661
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: 128
- eval_batch_size: 512
- 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_steps: 500
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 120 | 0.6514 | 0.6248 |
| No log | 2.0 | 240 | 0.5753 | 0.7198 |
| No log | 3.0 | 360 | 0.6240 | 0.6720 |
| No log | 4.0 | 480 | 0.4622 | 0.7847 |
| 0.6066 | 5.0 | 600 | 0.5026 | 0.7693 |
| 0.6066 | 6.0 | 720 | 0.4972 | 0.7817 |
| 0.6066 | 7.0 | 840 | 0.4209 | 0.7947 |
| 0.6066 | 8.0 | 960 | 0.4197 | 0.8142 |
| 0.4452 | 9.0 | 1080 | 0.5085 | 0.7935 |
| 0.4452 | 10.0 | 1200 | 0.3948 | 0.8265 |
| 0.4452 | 11.0 | 1320 | 0.3898 | 0.8307 |
| 0.4452 | 12.0 | 1440 | 0.3542 | 0.8490 |
| 0.322 | 13.0 | 1560 | 0.4070 | 0.8342 |
| 0.322 | 14.0 | 1680 | 0.3532 | 0.8454 |
| 0.322 | 15.0 | 1800 | 0.4472 | 0.8319 |
| 0.322 | 16.0 | 1920 | 0.3935 | 0.8549 |
| 0.2358 | 17.0 | 2040 | 0.3641 | 0.8625 |
| 0.2358 | 18.0 | 2160 | 0.3950 | 0.8614 |
| 0.2358 | 19.0 | 2280 | 0.4140 | 0.8655 |
| 0.2358 | 20.0 | 2400 | 0.4209 | 0.8661 |
Framework versions
- Transformers 4.53.0
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.2