|
--- |
|
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct |
|
library_name: peft |
|
license: llama3.1 |
|
tags: |
|
- trl |
|
- sft |
|
- generated_from_trainer |
|
model-index: |
|
- name: Llama-31-8B_task-3_180-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-3_180-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 None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.3360 |
|
|
|
## 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 | |
|
|:-------------:|:-------:|:----:|:---------------:| |
|
| 1.674 | 0.9412 | 8 | 1.6584 | |
|
| 1.5596 | 2.0 | 17 | 1.5302 | |
|
| 1.4536 | 2.9412 | 25 | 1.4046 | |
|
| 1.1955 | 4.0 | 34 | 1.2397 | |
|
| 1.1221 | 4.9412 | 42 | 1.1855 | |
|
| 1.1181 | 6.0 | 51 | 1.1592 | |
|
| 1.1246 | 6.9412 | 59 | 1.1434 | |
|
| 1.0507 | 8.0 | 68 | 1.1335 | |
|
| 0.9763 | 8.9412 | 76 | 1.1265 | |
|
| 0.9776 | 10.0 | 85 | 1.1260 | |
|
| 0.929 | 10.9412 | 93 | 1.1289 | |
|
| 0.8679 | 12.0 | 102 | 1.1548 | |
|
| 0.8616 | 12.9412 | 110 | 1.1690 | |
|
| 0.815 | 14.0 | 119 | 1.2061 | |
|
| 0.6912 | 14.9412 | 127 | 1.2300 | |
|
| 0.6046 | 16.0 | 136 | 1.2953 | |
|
| 0.5919 | 16.9412 | 144 | 1.3360 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.12.0 |
|
- Transformers 4.44.0 |
|
- Pytorch 2.1.2+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |