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---
license: llama2
base_model: meta-llama/Llama-2-7b-chat-hf
tags:
- generated_from_trainer
model-index:
- name: MSc_llama2_finetuned_model_secondData3
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_secondData3
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: 0.6783
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 3.9959 | 1.33 | 10 | 3.6441 |
| 3.376 | 2.67 | 20 | 2.9540 |
| 2.6309 | 4.0 | 30 | 2.1878 |
| 1.9511 | 5.33 | 40 | 1.7018 |
| 1.6088 | 6.67 | 50 | 1.4477 |
| 1.3311 | 8.0 | 60 | 1.1180 |
| 0.9548 | 9.33 | 70 | 0.8536 |
| 0.8083 | 10.67 | 80 | 0.8007 |
| 0.7523 | 12.0 | 90 | 0.7644 |
| 0.6984 | 13.33 | 100 | 0.7371 |
| 0.6687 | 14.67 | 110 | 0.7191 |
| 0.634 | 16.0 | 120 | 0.7079 |
| 0.6045 | 17.33 | 130 | 0.6965 |
| 0.592 | 18.67 | 140 | 0.6902 |
| 0.5726 | 20.0 | 150 | 0.6868 |
| 0.5574 | 21.33 | 160 | 0.6824 |
| 0.5398 | 22.67 | 170 | 0.6813 |
| 0.5364 | 24.0 | 180 | 0.6807 |
| 0.5288 | 25.33 | 190 | 0.6793 |
| 0.5219 | 26.67 | 200 | 0.6790 |
| 0.5217 | 28.0 | 210 | 0.6796 |
| 0.5175 | 29.33 | 220 | 0.6785 |
| 0.5117 | 30.67 | 230 | 0.6787 |
| 0.5167 | 32.0 | 240 | 0.6780 |
| 0.5136 | 33.33 | 250 | 0.6783 |
### Framework versions
- PEFT 0.4.0
- Transformers 4.38.2
- Pytorch 2.3.1+cu121
- Datasets 2.13.1
- Tokenizers 0.15.2
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