metadata
license: llama3
base_model: meta-llama/Meta-Llama-3-8B
tags:
- generated_from_trainer
model-index:
- name: MSc_llama3_finetuned_model_secondData
results: []
library_name: peft
MSc_llama3_finetuned_model_secondData
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7698
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- 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 |
|---|---|---|---|
| 3.7636 | 1.36 | 10 | 3.3566 |
| 2.8254 | 2.71 | 20 | 2.0280 |
| 1.5642 | 4.07 | 30 | 1.2681 |
| 1.1877 | 5.42 | 40 | 1.1017 |
| 1.0503 | 6.78 | 50 | 1.0240 |
| 0.9732 | 8.14 | 60 | 0.9786 |
| 0.9065 | 9.49 | 70 | 0.9394 |
| 0.8513 | 10.85 | 80 | 0.9004 |
| 0.7914 | 12.2 | 90 | 0.8791 |
| 0.7408 | 13.56 | 100 | 0.8509 |
| 0.6882 | 14.92 | 110 | 0.8191 |
| 0.6389 | 16.27 | 120 | 0.7877 |
| 0.5855 | 17.63 | 130 | 0.7748 |
| 0.5293 | 18.98 | 140 | 0.7502 |
| 0.4876 | 20.34 | 150 | 0.7337 |
| 0.4619 | 21.69 | 160 | 0.7275 |
| 0.4458 | 23.05 | 170 | 0.7315 |
| 0.4287 | 24.41 | 180 | 0.7475 |
| 0.434 | 25.76 | 190 | 0.7489 |
| 0.4186 | 27.12 | 200 | 0.7573 |
| 0.4158 | 28.47 | 210 | 0.7618 |
| 0.4105 | 29.83 | 220 | 0.7719 |
| 0.4039 | 31.19 | 230 | 0.7677 |
| 0.4087 | 32.54 | 240 | 0.7692 |
| 0.4078 | 33.9 | 250 | 0.7698 |
Framework versions
- PEFT 0.4.0
- Transformers 4.38.2
- Pytorch 2.3.1+cu121
- Datasets 2.13.1
- Tokenizers 0.15.2