|
--- |
|
license: apache-2.0 |
|
library_name: peft |
|
tags: |
|
- generated_from_trainer |
|
base_model: meta-llama/Meta-Llama-3-8B-Instruct |
|
model-index: |
|
- name: LLAMA3-8BI-APPS |
|
results: [] |
|
datasets: |
|
- codeparrot/apps |
|
metrics: |
|
- accuracy |
|
- bleu |
|
- rouge |
|
pipeline_tag: text-generation |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# LLAMA3-8BI-APPS |
|
|
|
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.1490 |
|
|
|
## 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: 5e-06 |
|
- train_batch_size: 4 |
|
- eval_batch_size: 4 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 16 |
|
- total_train_batch_size: 64 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_steps: 100 |
|
- training_steps: 1000 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 0.9027 | 0.1 | 100 | 0.9320 | |
|
| 0.8632 | 0.2 | 200 | 0.9143 | |
|
| 0.8572 | 0.3 | 300 | 1.0150 | |
|
| 0.937 | 0.4 | 400 | 1.0545 | |
|
| 1.0336 | 0.5 | 500 | 1.1029 | |
|
| 1.0056 | 0.6 | 600 | 1.1267 | |
|
| 1.0125 | 0.7 | 700 | 1.1307 | |
|
| 1.028 | 0.8 | 800 | 1.1398 | |
|
| 1.0692 | 0.9 | 900 | 1.1482 | |
|
| 1.0361 | 1.0 | 1000 | 1.1490 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.9.0 |
|
- Transformers 4.38.2 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
