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llama-ad-gen
This model is a fine-tuned version of meta-llama/Llama-2-7b-chat-hf on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6105
 
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: 8
 - eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: constant
 - lr_scheduler_warmup_ratio: 0.03
 - training_steps: 100
 - mixed_precision_training: Native AMP
 
Training results
| Training Loss | Epoch | Step | Validation Loss | 
|---|---|---|---|
| 0.789 | 0.25 | 25 | 0.8160 | 
| 0.5458 | 0.5 | 50 | 0.6579 | 
| 0.4236 | 0.75 | 75 | 0.6201 | 
| 0.339 | 1.0 | 100 | 0.6105 | 
Framework versions
- Transformers 4.35.0.dev0
 - Pytorch 2.1.0
 - Datasets 2.12.0
 - Tokenizers 0.14.1
 
Training procedure
The following bitsandbytes quantization config was used during training:
- quant_method: QuantizationMethod.BITS_AND_BYTES
 - 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: True
 - bnb_4bit_compute_dtype: float16
 
Framework versions
- PEFT 0.6.0.dev0