---
license: llama3
base_model: meta-llama/Meta-Llama-3-8B-Instruct
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-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7658

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 3.7986        | 1.36  | 10   | 3.3486          |
| 2.781         | 2.71  | 20   | 1.9851          |
| 1.6096        | 4.07  | 30   | 1.3075          |
| 1.2107        | 5.42  | 40   | 1.1210          |
| 1.0597        | 6.78  | 50   | 1.0222          |
| 0.9672        | 8.14  | 60   | 0.9562          |
| 0.8924        | 9.49  | 70   | 0.9131          |
| 0.8189        | 10.85 | 80   | 0.8582          |
| 0.7393        | 12.2  | 90   | 0.7907          |
| 0.6355        | 13.56 | 100  | 0.7136          |
| 0.5683        | 14.92 | 110  | 0.7013          |
| 0.533         | 16.27 | 120  | 0.7011          |
| 0.5155        | 17.63 | 130  | 0.7049          |
| 0.4965        | 18.98 | 140  | 0.7194          |
| 0.4826        | 20.34 | 150  | 0.7222          |
| 0.4617        | 21.69 | 160  | 0.7294          |
| 0.453         | 23.05 | 170  | 0.7347          |
| 0.439         | 24.41 | 180  | 0.7418          |
| 0.4333        | 25.76 | 190  | 0.7473          |
| 0.4261        | 27.12 | 200  | 0.7600          |
| 0.4238        | 28.47 | 210  | 0.7580          |
| 0.4163        | 29.83 | 220  | 0.7646          |
| 0.4158        | 31.19 | 230  | 0.7659          |
| 0.4137        | 32.54 | 240  | 0.7662          |
| 0.4131        | 33.9  | 250  | 0.7658          |


### Framework versions

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