| --- |
| base_model: meta-llama/Meta-Llama-3-8B-Instruct |
| library_name: peft |
| license: llama3 |
| tags: |
| - trl |
| - sft |
| - generated_from_trainer |
| model-index: |
| - name: experiments |
| 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. --> |
|
|
| # experiments |
|
|
| 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: 1.4332 |
|
|
| ## Model description |
|
|
| ``` |
| |
| MODEL_NAME = "/content/blackhole33/llama-5000-sample-peft" |
| quantization_config = BitsAndBytesConfig( |
| load_in_4bit=True, bnb_4bit_quant_type="nf4", bnb_4bit_compute_dtype=torch.bfloat16 |
| ) |
| |
| tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, use_fast=True) |
| |
| model = AutoModelForCausalLM.from_pretrained( |
| MODEL_NAME, quantization_config=quantization_config, device_map="auto" |
| ) |
| |
| ``` |
|
|
| ## 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: 2 |
| - eval_batch_size: 2 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 8 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: constant |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 1 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 1.3475 | 0.2 | 100 | 1.5142 | |
| | 1.4979 | 0.4 | 200 | 1.4703 | |
| | 1.4307 | 0.6 | 300 | 1.4510 | |
| | 1.3795 | 0.8 | 400 | 1.4434 | |
| | 1.3847 | 1.0 | 500 | 1.4332 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.12.0 |
| - Transformers 4.44.1 |
| - Pytorch 2.3.1+cu121 |
| - Datasets 2.21.0 |
| - Tokenizers 0.19.1 |
