|
|
--- |
|
|
license: llama3 |
|
|
library_name: peft |
|
|
tags: |
|
|
- alignment-handbook |
|
|
- trl |
|
|
- sft |
|
|
- generated_from_trainer |
|
|
base_model: meta-llama/Meta-Llama-3-8B-Instruct |
|
|
datasets: |
|
|
- nthakur/nomiracl-instruct |
|
|
model-index: |
|
|
- name: Meta-Llama-3-8B-Instruct-nomiracl-sft |
|
|
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. --> |
|
|
|
|
|
# Meta-Llama-3-8B-Instruct-nomiracl-sft |
|
|
|
|
|
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 the nthakur/nomiracl-instruct dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 1.6358 |
|
|
|
|
|
## 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: 1e-05 |
|
|
- train_batch_size: 4 |
|
|
- eval_batch_size: 4 |
|
|
- seed: 42 |
|
|
- distributed_type: multi-GPU |
|
|
- num_devices: 4 |
|
|
- gradient_accumulation_steps: 2 |
|
|
- total_train_batch_size: 32 |
|
|
- total_eval_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: 1 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|
|:-------------:|:------:|:----:|:---------------:| |
|
|
| 1.6576 | 0.2981 | 200 | 1.6656 | |
|
|
| 1.6447 | 0.5961 | 400 | 1.6409 | |
|
|
| 1.6245 | 0.8942 | 600 | 1.6358 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- PEFT 0.7.1 |
|
|
- Transformers 4.41.2 |
|
|
- Pytorch 2.3.0+cu121 |
|
|
- Datasets 2.20.0 |
|
|
- Tokenizers 0.19.1 |
