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: 0.4555
- F1 Macro: 0.8329
- F1: 0.8864
- F1 Neg: 0.7794
- Acc: 0.85
- Prec: 0.9035
- Recall: 0.8699
- Mcc: 0.6670
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 |
|---|---|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 497 | 0.4926 | 0.7671 | 0.8270 | 0.7071 | 0.7825 | 0.8421 | 0.8125 | 0.5350 |
| 0.6271 | 2.0 | 994 | 0.4256 | 0.7808 | 0.8608 | 0.7008 | 0.81 | 0.8103 | 0.9180 | 0.5762 |
| 0.4307 | 3.0 | 1491 | 0.4918 | 0.8193 | 0.8726 | 0.7660 | 0.835 | 0.8626 | 0.8828 | 0.6390 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2