metadata
base_model: meta-llama/Meta-Llama-3-8B-Instruct
datasets:
- nthakur/mirage-meta-llama-3-sft-instruct
library_name: peft
license: llama3
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: Meta-Llama-3-8B-Instruct-mirage-meta-llama-3-sft-instruct
results: []
Meta-Llama-3-8B-Instruct-mirage-meta-llama-3-sft-instruct
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the nthakur/mirage-meta-llama-3-sft-instruct dataset. It achieves the following results on the evaluation set:
- Loss: 0.2431
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: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.3403 | 0.0597 | 200 | 0.3074 |
| 0.3224 | 0.1195 | 400 | 0.2954 |
| 0.3055 | 0.1792 | 600 | 0.2886 |
| 0.2899 | 0.2389 | 800 | 0.2804 |
| 0.3116 | 0.2987 | 1000 | 0.2772 |
| 0.3101 | 0.3584 | 1200 | 0.2728 |
| 0.2913 | 0.4182 | 1400 | 0.2679 |
| 0.2765 | 0.4779 | 1600 | 0.2625 |
| 0.2697 | 0.5376 | 1800 | 0.2601 |
| 0.2759 | 0.5974 | 2000 | 0.2557 |
| 0.264 | 0.6571 | 2200 | 0.2524 |
| 0.2705 | 0.7168 | 2400 | 0.2490 |
| 0.2694 | 0.7766 | 2600 | 0.2466 |
| 0.2639 | 0.8363 | 2800 | 0.2450 |
| 0.2598 | 0.8961 | 3000 | 0.2435 |
| 0.2483 | 0.9558 | 3200 | 0.2432 |
Framework versions
- PEFT 0.10.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1