LORA_trained_on_MMLU_5shot_test
This model is a fine-tuned version of justshao/llama2-test on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5586
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- 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 |
---|---|---|---|
0.5992 | 1.0 | 877 | 0.5707 |
0.5572 | 2.0 | 1755 | 0.5622 |
0.541 | 3.0 | 2632 | 0.5613 |
0.5304 | 4.0 | 3510 | 0.5583 |
0.5259 | 5.0 | 4385 | 0.5586 |
Framework versions
- PEFT 0.10.0
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for justshao/LORA_trained_on_MMLU_5shot_test
Base model
justshao/llama2-test