metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
model-index:
- name: results
results: []
results
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: 0.6851
- F1: 0.8263
- F1 Macro: 0.8254
- F1 Micro: 0.8275
- Precision: 0.8312
- Precision Macro: 0.8328
- Precision Micro: 0.8275
- Recall: 0.8275
- Recall Macro: 0.8241
- Recall Micro: 0.8275
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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: constant
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | F1 Macro | F1 Micro | Precision | Precision Macro | Precision Micro | Recall | Recall Macro | Recall Micro |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 160 | 0.3593 | 0.8310 | 0.8307 | 0.8310 | 0.8312 | 0.8305 | 0.8310 | 0.8310 | 0.8309 | 0.8310 |
| No log | 2.0 | 320 | 0.4292 | 0.8290 | 0.8279 | 0.8310 | 0.8394 | 0.8419 | 0.8310 | 0.8310 | 0.8264 | 0.8310 |
| No log | 3.0 | 480 | 0.6851 | 0.8263 | 0.8254 | 0.8275 | 0.8312 | 0.8328 | 0.8275 | 0.8275 | 0.8241 | 0.8275 |
Framework versions
- Transformers 4.48.0
- Pytorch 2.5.0+cu124
- Datasets 2.16.1
- Tokenizers 0.21.1