metadata
base_model: vinai/bertweet-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bertweet-large_epoch3_batch4_lr2e-05_w0.01
results: []
bertweet-large_epoch3_batch4_lr2e-05_w0.01
This model is a fine-tuned version of vinai/bertweet-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5167
- Accuracy: 0.9066
- F1: 0.8768
- Precision: 0.8617
- Recall: 0.8925
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.6423 | 1.0 | 788 | 0.4273 | 0.8966 | 0.8597 | 0.8689 | 0.8507 |
| 0.4072 | 2.0 | 1576 | 0.5435 | 0.8910 | 0.8600 | 0.8247 | 0.8985 |
| 0.2823 | 3.0 | 2364 | 0.5167 | 0.9066 | 0.8768 | 0.8617 | 0.8925 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3