---
license: llama3
base_model: meta-llama/Meta-Llama-3-8B
tags:
- generated_from_trainer
model-index:
- name: MSc_llama3_finetuned_model_secondData
  results: []
library_name: peft
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# MSc_llama3_finetuned_model_secondData

This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9224

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure


The following `bitsandbytes` quantization config was used during training:
- quant_method: bitsandbytes
- _load_in_8bit: False
- _load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: bfloat16
- load_in_4bit: True
- load_in_8bit: False
### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- training_steps: 250

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.791         | 1.33  | 10   | 3.6476          |
| 3.2811        | 2.67  | 20   | 2.9195          |
| 2.3899        | 4.0   | 30   | 1.8723          |
| 1.5443        | 5.33  | 40   | 1.3519          |
| 1.2394        | 6.67  | 50   | 1.1884          |
| 1.1162        | 8.0   | 60   | 1.1023          |
| 1.0377        | 9.33  | 70   | 1.0551          |
| 0.9831        | 10.67 | 80   | 1.0228          |
| 0.9476        | 12.0  | 90   | 0.9988          |
| 0.9032        | 13.33 | 100  | 0.9850          |
| 0.8799        | 14.67 | 110  | 0.9668          |
| 0.8581        | 16.0  | 120  | 0.9503          |
| 0.8315        | 17.33 | 130  | 0.9457          |
| 0.8077        | 18.67 | 140  | 0.9422          |
| 0.7921        | 20.0  | 150  | 0.9362          |
| 0.7752        | 21.33 | 160  | 0.9318          |
| 0.7614        | 22.67 | 170  | 0.9306          |
| 0.7559        | 24.0  | 180  | 0.9233          |
| 0.7441        | 25.33 | 190  | 0.9237          |
| 0.7345        | 26.67 | 200  | 0.9237          |
| 0.7341        | 28.0  | 210  | 0.9205          |
| 0.7288        | 29.33 | 220  | 0.9195          |
| 0.7237        | 30.67 | 230  | 0.9219          |
| 0.7255        | 32.0  | 240  | 0.9210          |
| 0.7273        | 33.33 | 250  | 0.9224          |


### Framework versions

- PEFT 0.4.0
- Transformers 4.38.2
- Pytorch 2.3.1+cu121
- Datasets 2.13.1
- Tokenizers 0.15.2