BERTweet-large-full-match-labels
This model is a fine-tuned version of vinai/bertweet-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3179
- Accuracy: 0.8944
- F1 Macro: 0.8872
- F1 Weighted: 0.8945
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: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted |
|---|---|---|---|---|---|---|
| 0.3934 | 1.0 | 749 | 0.3630 | 0.8681 | 0.8586 | 0.8691 |
| 0.2176 | 2.0 | 1498 | 0.3179 | 0.8944 | 0.8872 | 0.8945 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.9.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
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Model tree for ADS509/BERTweet-large-full-match-labels
Base model
vinai/bertweet-large