metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
- roc_auc
model-index:
- name: ModernEMO-large
results: []
datasets:
- Jsevisal/go_emotions_ekman
language:
- en
pipeline_tag: text-classification
ModernEMO-large
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: 0.2210
- F1: 0.6969
- Roc Auc: 0.8082
- Accuracy: 0.6196
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: 8e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.2365 | 1.0 | 5427 | 0.2099 | 0.6885 | 0.7980 | 0.5947 |
| 0.1665 | 2.0 | 10854 | 0.2210 | 0.6969 | 0.8082 | 0.6196 |
Framework versions
- Transformers 4.49.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0