lora-out
This model is a fine-tuned version of NousResearch/Llama-2-7b-hf on a synthetic recipe assistant dataset comprised of 2000 samples. It achieves the following results on the evaluation set:
- Loss: 0.8666
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: 6
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.9548 | 8.0 | 20 | 0.9240 |
| 0.8514 | 16.0 | 40 | 0.8523 |
| 0.7774 | 24.0 | 60 | 0.8498 |
| 0.7178 | 32.0 | 80 | 0.8597 |
| 0.7103 | 40.0 | 100 | 0.8666 |
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0
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Model tree for cadaeic/llama2-7b-recipe-lora
Base model
NousResearch/Llama-2-7b-hf