model1_absa_cont
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2382
- Precision: 0.2445
- Recall: 0.3046
- F1: 0.2712
- Accuracy: 0.5420
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 7 | 1.2382 | 0.2445 | 0.3046 | 0.2712 | 0.5420 |
| No log | 2.0 | 14 | 1.2382 | 0.2445 | 0.3046 | 0.2712 | 0.5420 |
| No log | 3.0 | 21 | 1.2382 | 0.2445 | 0.3046 | 0.2712 | 0.5420 |
| No log | 4.0 | 28 | 1.2382 | 0.2445 | 0.3046 | 0.2712 | 0.5420 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2