metadata
base_model: UBC-NLP/MARBERTv2
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: Model3_Marabertv2_T1_WS_A100
results: []
Model3_Marabertv2_T1_WS_A100
This model is a fine-tuned version of UBC-NLP/MARBERTv2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2316
- F1: 0.8336
- F1 Macro: 0.7718
- Roc Auc: 0.8974
- Accuracy: 0.8066
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | F1 Macro | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.2253 | 1.0 | 507 | 0.1618 | 0.8162 | 0.7404 | 0.8787 | 0.7814 |
| 0.1159 | 2.0 | 1014 | 0.1652 | 0.8273 | 0.7545 | 0.8928 | 0.8017 |
| 0.073 | 3.0 | 1521 | 0.1883 | 0.8355 | 0.7645 | 0.8996 | 0.8045 |
| 0.0454 | 4.0 | 2028 | 0.2138 | 0.8408 | 0.7700 | 0.9026 | 0.8128 |
| 0.0301 | 5.0 | 2535 | 0.2316 | 0.8336 | 0.7718 | 0.8974 | 0.8066 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3