experiment-model-bertweet
This model is a fine-tuned version of finiteautomata/bertweet-base-sentiment-analysis on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6847
- Accuracy: 0.8306
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.3532 | 1.0 | 760 | 0.3454 | 0.8453 |
0.2907 | 2.0 | 1521 | 0.3672 | 0.8465 |
0.2568 | 3.0 | 2281 | 0.4530 | 0.8393 |
0.2054 | 4.0 | 3042 | 0.5747 | 0.8369 |
0.1495 | 5.0 | 3800 | 0.6847 | 0.8306 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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