BERT-SA-LORA
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: 0.3017
- Accuracy: 0.8943
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: 0.0002
- train_batch_size: 8
- eval_batch_size: 16
- 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 |
|---|---|---|---|---|
| No log | 1.0 | 375 | 0.3246 | 0.8687 |
| 0.5095 | 2.0 | 750 | 0.3154 | 0.8803 |
| 0.3046 | 3.0 | 1125 | 0.2957 | 0.888 |
| 0.2754 | 4.0 | 1500 | 0.2971 | 0.8937 |
| 0.2754 | 5.0 | 1875 | 0.3017 | 0.8943 |
Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for Intradiction/BERT-SA-LORA
Base model
google-bert/bert-base-uncased