---
license: llama2
base_model: meta-llama/Llama-2-7b-chat-hf
tags:
- generated_from_trainer
model-index:
- name: MSc_llama2_finetuned_model_updatePara
  results: []
library_name: peft
---

<!-- 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. -->

# MSc_llama2_finetuned_model_updatePara

This model is a fine-tuned version of [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4329

## 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: 0.0001
- 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: 0.1
- training_steps: 400

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 16.5659       | 1.21  | 10   | 1.7444          |
| 1.1543        | 2.42  | 20   | 0.8871          |
| 0.7821        | 3.64  | 30   | 0.6674          |
| 0.6295        | 4.85  | 40   | 0.5773          |
| 0.5642        | 6.06  | 50   | 0.5303          |
| 0.5251        | 7.27  | 60   | 0.4983          |
| 0.4969        | 8.48  | 70   | 0.4813          |
| 0.4805        | 9.7   | 80   | 0.4689          |
| 0.4702        | 10.91 | 90   | 0.4585          |
| 0.4651        | 12.12 | 100  | 0.4512          |
| 0.4472        | 13.33 | 110  | 0.4462          |
| 0.4466        | 14.55 | 120  | 0.4415          |
| 0.4413        | 15.76 | 130  | 0.4385          |
| 0.4398        | 16.97 | 140  | 0.4398          |
| 0.4314        | 18.18 | 150  | 0.4382          |
| 0.4313        | 19.39 | 160  | 0.4313          |
| 0.4314        | 20.61 | 170  | 0.4294          |
| 0.4189        | 21.82 | 180  | 0.4279          |
| 0.4203        | 23.03 | 190  | 0.4285          |
| 0.4164        | 24.24 | 200  | 0.4279          |
| 0.4183        | 25.45 | 210  | 0.4268          |
| 0.4107        | 26.67 | 220  | 0.4268          |
| 0.4068        | 27.88 | 230  | 0.4252          |
| 0.4082        | 29.09 | 240  | 0.4266          |
| 0.4074        | 30.3  | 250  | 0.4299          |
| 0.4025        | 31.52 | 260  | 0.4266          |
| 0.4038        | 32.73 | 270  | 0.4264          |
| 0.4008        | 33.94 | 280  | 0.4284          |
| 0.4002        | 35.15 | 290  | 0.4279          |
| 0.3937        | 36.36 | 300  | 0.4307          |
| 0.4033        | 37.58 | 310  | 0.4299          |
| 0.3974        | 38.79 | 320  | 0.4307          |
| 0.3951        | 40.0  | 330  | 0.4312          |
| 0.3948        | 41.21 | 340  | 0.4327          |
| 0.3971        | 42.42 | 350  | 0.4321          |
| 0.3958        | 43.64 | 360  | 0.4327          |
| 0.3906        | 44.85 | 370  | 0.4333          |
| 0.3977        | 46.06 | 380  | 0.4328          |
| 0.3956        | 47.27 | 390  | 0.4330          |
| 0.3956        | 48.48 | 400  | 0.4329          |


### Framework versions

- PEFT 0.4.0
- Transformers 4.38.2
- Pytorch 2.3.0+cu121
- Datasets 2.13.1
- Tokenizers 0.15.2