metadata
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
datasets:
- GaetanMichelet/chat-60_ft_task-2_auto
- GaetanMichelet/chat-120_ft_task-2_auto
library_name: peft
license: llama3.1
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: Llama-31-8B_task-2_120-samples_config-1_full_auto
results: []
Llama-31-8B_task-2_120-samples_config-1_full_auto
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the GaetanMichelet/chat-60_ft_task-2_auto and the GaetanMichelet/chat-120_ft_task-2_auto datasets. It achieves the following results on the evaluation set:
- Loss: 0.9959
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
- gradient_accumulation_steps: 8
- total_train_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: 50
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.4871 | 1.0 | 11 | 1.4805 |
1.2753 | 2.0 | 22 | 1.3422 |
1.1856 | 3.0 | 33 | 1.1891 |
1.0973 | 4.0 | 44 | 1.0591 |
1.0204 | 5.0 | 55 | 1.0277 |
0.9819 | 6.0 | 66 | 1.0086 |
0.948 | 7.0 | 77 | 0.9993 |
0.9103 | 8.0 | 88 | 0.9959 |
0.8302 | 9.0 | 99 | 1.0063 |
0.7247 | 10.0 | 110 | 1.0327 |
0.7159 | 11.0 | 121 | 1.0794 |
0.5506 | 12.0 | 132 | 1.1349 |
0.5606 | 13.0 | 143 | 1.1961 |
0.3523 | 14.0 | 154 | 1.2591 |
0.2739 | 15.0 | 165 | 1.3140 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1