ABSA-SentencePair-DAPT-HARDSubsample60089-bert-base-Camel-MSA-ru2
This model is a fine-tuned version of salohnana2018/CAMEL-domianAdaption-Single-ABSA-HardSample on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4543
- Accuracy: 0.8852
- F1: 0.8852
- Precision: 0.8852
- Recall: 0.8852
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: 32
- eval_batch_size: 32
- seed: 42
- 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 | F1 | Precision | Recall |
---|---|---|---|---|---|---|---|
0.4264 | 1.0 | 265 | 0.3527 | 0.8611 | 0.8611 | 0.8611 | 0.8611 |
0.304 | 2.0 | 530 | 0.3400 | 0.8828 | 0.8828 | 0.8828 | 0.8828 |
0.2282 | 3.0 | 795 | 0.3840 | 0.8790 | 0.8790 | 0.8790 | 0.8790 |
0.1614 | 4.0 | 1060 | 0.4024 | 0.8856 | 0.8856 | 0.8856 | 0.8856 |
0.1075 | 5.0 | 1325 | 0.4543 | 0.8852 | 0.8852 | 0.8852 | 0.8852 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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