metadata
base_model: UBC-NLP/MARBERTv2
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: OTE-NoDapt-ABSA-bert-base-MARBERTv2-DefultHp-FineTune
results: []
OTE-NoDapt-ABSA-bert-base-MARBERTv2-DefultHp-FineTune
This model is a fine-tuned version of UBC-NLP/MARBERTv2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1278
- Precision: 0.7571
- Recall: 0.7843
- F1: 0.7704
- Accuracy: 0.9549
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 |
|---|---|---|---|---|---|---|---|
| 0.1919 | 1.0 | 121 | 0.1168 | 0.7751 | 0.7265 | 0.7500 | 0.9537 |
| 0.0949 | 2.0 | 242 | 0.1188 | 0.7863 | 0.7588 | 0.7723 | 0.9568 |
| 0.0703 | 3.0 | 363 | 0.1278 | 0.7571 | 0.7843 | 0.7704 | 0.9549 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3