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: 0.4366
- F1 Macro: 0.8302
- F1: 0.8917
- F1 Neg: 0.7686
- Acc: 0.8525
- Prec: 0.8804
- Recall: 0.9033
- Mcc: 0.6610
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 |
|---|---|---|---|---|---|---|---|---|---|---|
| 0.6636 | 1.0 | 614 | 0.5643 | 0.6935 | 0.8191 | 0.5678 | 0.745 | 0.75 | 0.9023 | 0.4193 |
| 0.5206 | 2.0 | 1228 | 0.6205 | 0.7341 | 0.7640 | 0.7042 | 0.7375 | 0.8995 | 0.6641 | 0.5116 |
| 0.4363 | 3.0 | 1842 | 0.5409 | 0.7997 | 0.8673 | 0.7321 | 0.8225 | 0.8315 | 0.9062 | 0.6059 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2