metadata
language:
- zh
license: other
library_name: peft
tags:
- trl
- sft
- nycu-112-2-deeplearning-hw2
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B-Instruct
datasets:
- DandinPower/ZH-Reading-Comprehension-Llama-Instruct
model-index:
- name: llama_3_8b_lora_completion_only
results: []
llama_3_8b_lora_completion_only
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the DandinPower/ZH-Reading-Comprehension-Llama-Instruct dataset. It achieves the following results on the evaluation set:
- Loss: 0.0924
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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- total_eval_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 700
- num_epochs: 5.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.105 | 0.3690 | 250 | 0.0762 |
| 0.0716 | 0.7380 | 500 | 0.0897 |
| 0.0652 | 1.1070 | 750 | 0.0832 |
| 0.061 | 1.4760 | 1000 | 0.0640 |
| 0.0373 | 1.8450 | 1250 | 0.0813 |
| 0.0344 | 2.2140 | 1500 | 0.0686 |
| 0.0207 | 2.5830 | 1750 | 0.0662 |
| 0.0351 | 2.9520 | 2000 | 0.0669 |
| 0.0028 | 3.3210 | 2250 | 0.0996 |
| 0.0101 | 3.6900 | 2500 | 0.0718 |
| 0.0044 | 4.0590 | 2750 | 0.0825 |
| 0.0123 | 4.4280 | 3000 | 0.0969 |
| 0.0031 | 4.7970 | 3250 | 0.0924 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1