metadata
base_model: vinai/bertweet-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: BERTweet
results: []
BERTweet
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: 0.2836
- Accuracy: 0.9070
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: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.6594 | 0.0994 | 47 | 0.5265 | 0.7661 |
0.4744 | 0.1987 | 94 | 0.5127 | 0.7736 |
0.389 | 0.2981 | 141 | 0.4142 | 0.8441 |
0.4078 | 0.3975 | 188 | 0.3744 | 0.8778 |
0.344 | 0.4968 | 235 | 0.4091 | 0.8516 |
0.3149 | 0.5962 | 282 | 0.3440 | 0.8853 |
0.3883 | 0.6956 | 329 | 0.3599 | 0.8741 |
0.3254 | 0.7949 | 376 | 0.3196 | 0.9055 |
0.3261 | 0.8943 | 423 | 0.2935 | 0.9055 |
0.3308 | 0.9937 | 470 | 0.2836 | 0.9070 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1