---
license: llama2
base_model: meta-llama/Llama-2-7b-chat-hf
tags:
- generated_from_trainer
model-index:
- name: MSc_llama2_finetuned_model_secondData8
  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_secondData8

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: 0.6809

## 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: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 3.9839        | 1.33  | 10   | 3.6565          |
| 3.3873        | 2.67  | 20   | 2.9922          |
| 2.6379        | 4.0   | 30   | 2.2276          |
| 1.9614        | 5.33  | 40   | 1.7433          |
| 1.6082        | 6.67  | 50   | 1.4612          |
| 1.3139        | 8.0   | 60   | 1.1369          |
| 0.9676        | 9.33  | 70   | 0.8804          |
| 0.8286        | 10.67 | 80   | 0.8272          |
| 0.7654        | 12.0  | 90   | 0.7804          |
| 0.7181        | 13.33 | 100  | 0.7474          |
| 0.6712        | 14.67 | 110  | 0.7286          |
| 0.6433        | 16.0  | 120  | 0.7128          |
| 0.6169        | 17.33 | 130  | 0.6997          |
| 0.5964        | 18.67 | 140  | 0.6971          |
| 0.5806        | 20.0  | 150  | 0.6893          |
| 0.5669        | 21.33 | 160  | 0.6867          |
| 0.5472        | 22.67 | 170  | 0.6861          |
| 0.5538        | 24.0  | 180  | 0.6819          |
| 0.535         | 25.33 | 190  | 0.6816          |
| 0.5322        | 26.67 | 200  | 0.6825          |
| 0.5333        | 28.0  | 210  | 0.6818          |
| 0.5203        | 29.33 | 220  | 0.6813          |
| 0.5259        | 30.67 | 230  | 0.6812          |
| 0.5264        | 32.0  | 240  | 0.6812          |
| 0.5209        | 33.33 | 250  | 0.6809          |


### Framework versions

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