llama2-7b-tuned-qna
This model is a fine-tuned version of genaitraining/llama-2-7b-domain-tuned on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 0.7823
Model description
More information needed
Intended uses & limitations
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Training and evaluation data
More information needed
Training procedure
The following bitsandbytes quantization config was used during training:
- quant_method: bitsandbytes
- _load_in_8bit: False
- _load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float16
- bnb_4bit_quant_storage: uint8
- load_in_4bit: True
- load_in_8bit: False
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.821 | 1.0 | 8859 | 0.7823 |
Framework versions
- PEFT 0.4.0
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.13.0
- Tokenizers 0.19.1
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Model tree for smrynrz20/llama2-7b-tuned-qna
Base model
genaitraining/llama-2-7b-domain-tuned