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OTE-domianAdaption-ABSA-Qarib-HARD-SemEval-run1
This model is a fine-tuned version of salohnana2018/Qarib-domianAdaption-OTE-ABSA-HARD-SemEvlLast on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1350
- Precision: 0.7502
- Recall: 0.7872
- F1: 0.7683
- Accuracy: 0.9550
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: 8
- seed: 25
- 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 | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.149 | 1.0 | 121 | 0.1140 | 0.7800 | 0.7489 | 0.7641 | 0.9560 |
0.081 | 2.0 | 242 | 0.1174 | 0.7759 | 0.7573 | 0.7665 | 0.9563 |
0.051 | 3.0 | 363 | 0.1350 | 0.7502 | 0.7872 | 0.7683 | 0.9550 |
Framework versions
- Transformers 4.30.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3