---
license: llama2
base_model: meta-llama/Llama-2-7b-chat-hf
tags:
- generated_from_trainer
model-index:
- name: MSc_llama2_finetuned_model
  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_llama2_finetuned_model

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: 0.4323

## 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: 0.0002
- 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: 200

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 10.3286       | 1.21  | 10   | 0.9783          |
| 0.7962        | 2.42  | 20   | 0.6498          |
| 0.5916        | 3.64  | 30   | 0.5509          |
| 0.5269        | 4.85  | 40   | 0.5075          |
| 0.4919        | 6.06  | 50   | 0.4851          |
| 0.4764        | 7.27  | 60   | 0.4696          |
| 0.4626        | 8.48  | 70   | 0.4597          |
| 0.4529        | 9.7   | 80   | 0.4654          |
| 0.4522        | 10.91 | 90   | 0.4489          |
| 0.4417        | 12.12 | 100  | 0.4456          |
| 0.4347        | 13.33 | 110  | 0.4409          |
| 0.4328        | 14.55 | 120  | 0.4381          |
| 0.4288        | 15.76 | 130  | 0.4376          |
| 0.4232        | 16.97 | 140  | 0.4364          |
| 0.4225        | 18.18 | 150  | 0.4344          |
| 0.4216        | 19.39 | 160  | 0.4330          |
| 0.4194        | 20.61 | 170  | 0.4323          |
| 0.4178        | 21.82 | 180  | 0.4323          |
| 0.4176        | 23.03 | 190  | 0.4323          |
| 0.4171        | 24.24 | 200  | 0.4323          |


### Framework versions

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