FineTunedllema_nada
This model is a fine-tuned version of beomi/llama-2-ko-7b on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8265
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: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.9417 | 1.0 | 112 | 0.8217 |
0.7246 | 2.0 | 225 | 0.7960 |
0.5382 | 2.99 | 336 | 0.8265 |
Framework versions
- PEFT 0.7.2.dev0
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2
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Model tree for Nada81/FineTunedllema_nada
Base model
beomi/llama-2-ko-7b