metadata
license: llama2
base_model: meta-llama/Llama-2-7b-chat-hf
tags:
- generated_from_trainer
model-index:
- name: MSc_llama2_finetuned_model_updatePara
results: []
library_name: peft
MSc_llama2_finetuned_model_updatePara
This model is a fine-tuned version of meta-llama/Llama-2-7b-chat-hf on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4329
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 0.1
- training_steps: 400
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
16.5659 | 1.21 | 10 | 1.7444 |
1.1543 | 2.42 | 20 | 0.8871 |
0.7821 | 3.64 | 30 | 0.6674 |
0.6295 | 4.85 | 40 | 0.5773 |
0.5642 | 6.06 | 50 | 0.5303 |
0.5251 | 7.27 | 60 | 0.4983 |
0.4969 | 8.48 | 70 | 0.4813 |
0.4805 | 9.7 | 80 | 0.4689 |
0.4702 | 10.91 | 90 | 0.4585 |
0.4651 | 12.12 | 100 | 0.4512 |
0.4472 | 13.33 | 110 | 0.4462 |
0.4466 | 14.55 | 120 | 0.4415 |
0.4413 | 15.76 | 130 | 0.4385 |
0.4398 | 16.97 | 140 | 0.4398 |
0.4314 | 18.18 | 150 | 0.4382 |
0.4313 | 19.39 | 160 | 0.4313 |
0.4314 | 20.61 | 170 | 0.4294 |
0.4189 | 21.82 | 180 | 0.4279 |
0.4203 | 23.03 | 190 | 0.4285 |
0.4164 | 24.24 | 200 | 0.4279 |
0.4183 | 25.45 | 210 | 0.4268 |
0.4107 | 26.67 | 220 | 0.4268 |
0.4068 | 27.88 | 230 | 0.4252 |
0.4082 | 29.09 | 240 | 0.4266 |
0.4074 | 30.3 | 250 | 0.4299 |
0.4025 | 31.52 | 260 | 0.4266 |
0.4038 | 32.73 | 270 | 0.4264 |
0.4008 | 33.94 | 280 | 0.4284 |
0.4002 | 35.15 | 290 | 0.4279 |
0.3937 | 36.36 | 300 | 0.4307 |
0.4033 | 37.58 | 310 | 0.4299 |
0.3974 | 38.79 | 320 | 0.4307 |
0.3951 | 40.0 | 330 | 0.4312 |
0.3948 | 41.21 | 340 | 0.4327 |
0.3971 | 42.42 | 350 | 0.4321 |
0.3958 | 43.64 | 360 | 0.4327 |
0.3906 | 44.85 | 370 | 0.4333 |
0.3977 | 46.06 | 380 | 0.4328 |
0.3956 | 47.27 | 390 | 0.4330 |
0.3956 | 48.48 | 400 | 0.4329 |
Framework versions
- PEFT 0.4.0
- Transformers 4.38.2
- Pytorch 2.3.0+cu121
- Datasets 2.13.1
- Tokenizers 0.15.2