lora_fine_tuned_boolq_sloberta
This model is a fine-tuned version of EMBEDDIA/sloberta on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5648
- Accuracy: 0.7778
- F1: 0.6806
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 400
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.6767 | 4.1667 | 50 | 0.5823 | 0.7778 | 0.6806 |
0.6548 | 8.3333 | 100 | 0.5676 | 0.7778 | 0.6806 |
0.654 | 12.5 | 150 | 0.5688 | 0.7778 | 0.6806 |
0.6545 | 16.6667 | 200 | 0.5718 | 0.7778 | 0.6806 |
0.6521 | 20.8333 | 250 | 0.5688 | 0.7778 | 0.6806 |
0.6507 | 25.0 | 300 | 0.5654 | 0.7778 | 0.6806 |
0.6494 | 29.1667 | 350 | 0.5658 | 0.7778 | 0.6806 |
0.646 | 33.3333 | 400 | 0.5648 | 0.7778 | 0.6806 |
Framework versions
- PEFT 0.11.1
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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