metadata
base_model: meta-llama/Meta-Llama-3-8B
datasets:
- HuggingFaceH4/ultrachat_200k
library_name: peft
license: llama3
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: llama3-sudo-sanity
results: []
llama3-sudo-sanity
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the HuggingFaceH4/ultrachat_200k dataset. It achieves the following results on the evaluation set:
- Loss: 1.1030
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: 8
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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 |
|---|---|---|---|
| 1.8735 | 0.9899 | 49 | 1.8325 |
| 1.8231 | 2.0 | 99 | 1.7239 |
| 1.7516 | 2.9899 | 148 | 1.6330 |
| 1.6586 | 4.0 | 198 | 1.5280 |
| 1.5571 | 4.9899 | 247 | 1.4166 |
| 1.4677 | 6.0 | 297 | 1.3068 |
| 1.3422 | 6.9899 | 346 | 1.2082 |
| 1.2609 | 8.0 | 396 | 1.1378 |
| 1.1647 | 8.9899 | 445 | 1.1074 |
| 1.1571 | 9.8990 | 490 | 1.1030 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1