metadata
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
datasets:
- GaetanMichelet/chat-60_ft_task-1_auto
library_name: peft
license: llama3.1
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: Llama-31-8B_task-1_60-samples_config-2_full_auto
results: []
Llama-31-8B_task-1_60-samples_config-2_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-1_auto dataset. It achieves the following results on the evaluation set:
- Loss: 0.8270
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: 16
- total_train_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: 50
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.2096 | 0.6957 | 2 | 2.1129 |
2.167 | 1.7391 | 5 | 1.9558 |
1.8726 | 2.7826 | 8 | 1.7428 |
1.7678 | 3.8261 | 11 | 1.5017 |
1.3895 | 4.8696 | 14 | 1.2525 |
1.234 | 5.9130 | 17 | 1.0325 |
0.9378 | 6.9565 | 20 | 0.9271 |
0.8782 | 8.0 | 23 | 0.8920 |
0.8394 | 8.6957 | 25 | 0.8784 |
0.7845 | 9.7391 | 28 | 0.8647 |
0.7863 | 10.7826 | 31 | 0.8503 |
0.7261 | 11.8261 | 34 | 0.8417 |
0.7333 | 12.8696 | 37 | 0.8337 |
0.6709 | 13.9130 | 40 | 0.8289 |
0.6612 | 14.9565 | 43 | 0.8270 |
0.6253 | 16.0 | 46 | 0.8289 |
0.6012 | 16.6957 | 48 | 0.8323 |
0.5792 | 17.7391 | 51 | 0.8385 |
0.5162 | 18.7826 | 54 | 0.8561 |
0.5219 | 19.8261 | 57 | 0.8603 |
0.445 | 20.8696 | 60 | 0.8802 |
0.4396 | 21.9130 | 63 | 0.9046 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1