metadata
base_model: vinai/bertweet-base
tags:
- generated_from_trainer
metrics:
- f1
- recall
model-index:
- name: bertweet-base
results: []
bertweet-base
This model is a fine-tuned version of vinai/bertweet-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5120
- F1 Macro: 0.7346
- F1: 0.8315
- F1 Neg: 0.6378
- Acc: 0.77
- Prec: 0.7828
- Recall: 0.8867
- Mcc: 0.4829
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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 | F1 Neg | Acc | Prec | Recall | Mcc |
|---|---|---|---|---|---|---|---|---|---|---|
| 0.6427 | 1.0 | 600 | 0.6329 | 0.6619 | 0.6941 | 0.6298 | 0.665 | 0.8352 | 0.5938 | 0.3715 |
| 0.5445 | 2.0 | 1200 | 0.5193 | 0.7363 | 0.8233 | 0.6493 | 0.765 | 0.7935 | 0.8555 | 0.4770 |
| 0.4446 | 3.0 | 1800 | 0.5120 | 0.7346 | 0.8315 | 0.6378 | 0.77 | 0.7828 | 0.8867 | 0.4829 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2