--- license: llama2 base_model: meta-llama/Llama-2-7b-chat-hf tags: - generated_from_trainer model-index: - name: MSc_llama2_finetuned_model_secondData9 results: [] library_name: peft --- # MSc_llama2_finetuned_model_secondData9 This model is a fine-tuned version of [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.7454 ## Model description More information needed ## Intended uses & limitations More information needed ## 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: True - bnb_4bit_compute_dtype: bfloat16 - load_in_4bit: True - load_in_8bit: False ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 3e-05 - train_batch_size: 32 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 64 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.03 - training_steps: 250 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 4.0419 | 1.33 | 10 | 3.8603 | | 3.6394 | 2.67 | 20 | 3.4241 | | 3.165 | 4.0 | 30 | 2.8774 | | 2.6005 | 5.33 | 40 | 2.3073 | | 2.0686 | 6.67 | 50 | 1.8698 | | 1.7422 | 8.0 | 60 | 1.6598 | | 1.5451 | 9.33 | 70 | 1.4786 | | 1.3602 | 10.67 | 80 | 1.2727 | | 1.1005 | 12.0 | 90 | 0.9606 | | 0.871 | 13.33 | 100 | 0.8730 | | 0.8094 | 14.67 | 110 | 0.8396 | | 0.7729 | 16.0 | 120 | 0.8150 | | 0.7393 | 17.33 | 130 | 0.7961 | | 0.7087 | 18.67 | 140 | 0.7818 | | 0.6975 | 20.0 | 150 | 0.7702 | | 0.6765 | 21.33 | 160 | 0.7626 | | 0.6642 | 22.67 | 170 | 0.7570 | | 0.6555 | 24.0 | 180 | 0.7529 | | 0.6485 | 25.33 | 190 | 0.7503 | | 0.6416 | 26.67 | 200 | 0.7474 | | 0.6363 | 28.0 | 210 | 0.7464 | | 0.6403 | 29.33 | 220 | 0.7458 | | 0.6254 | 30.67 | 230 | 0.7455 | | 0.6347 | 32.0 | 240 | 0.7451 | | 0.6337 | 33.33 | 250 | 0.7454 | ### Framework versions - PEFT 0.4.0 - Transformers 4.38.2 - Pytorch 2.4.0+cu121 - Datasets 2.13.1 - Tokenizers 0.15.2