|
--- |
|
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: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# 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](https://huggingface.co/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 |
