gemma-ViMMRC-Answer
This model is a fine-tuned version of unsloth/gemma-1.1-7b-it-bnb-4bit on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1034
- Accuracy: 0.8493
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
- ViMMRC train and test set
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 3407
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 5
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
13.1 | 0.3306 | 10 | 5.9870 |
2.4875 | 0.6612 | 20 | 1.1997 |
0.5062 | 0.9917 | 30 | 0.2423 |
0.1602 | 1.3223 | 40 | 0.1251 |
0.1289 | 1.6529 | 50 | 0.1156 |
0.1234 | 1.9835 | 60 | 0.1000 |
0.0727 | 2.3140 | 70 | 0.1068 |
0.0945 | 2.6446 | 80 | 0.1035 |
0.0785 | 2.9752 | 90 | 0.1034 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1
- Downloads last month
- 1
Model tree for Angelectronic/gemma-ViMMRC-Answer
Base model
unsloth/gemma-1.1-7b-it-bnb-4bit