metadata
base_model: meta-llama/Meta-Llama-3-8B
datasets:
- generator
library_name: peft
license: llama3
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: llama3-8b-classification-gpt4o-100k
results: []
llama3-8b-classification-gpt4o-100k
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 2.0032
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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.9183 | 1.0 | 237 | 1.6517 |
0.8583 | 2.0 | 474 | 1.6295 |
0.8179 | 3.0 | 711 | 1.6559 |
0.7533 | 4.0 | 948 | 1.6894 |
0.716 | 5.0 | 1185 | 1.7251 |
0.6876 | 6.0 | 1422 | 1.7830 |
0.6344 | 7.0 | 1659 | 1.8557 |
0.591 | 8.0 | 1896 | 1.9240 |
0.5677 | 9.0 | 2133 | 1.9842 |
0.5648 | 10.0 | 2370 | 2.0032 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1