---
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