MSc_llama2_finetuned_model_secondData9
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: 0.7454
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
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Base model
meta-llama/Llama-2-7b-chat-hf