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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_secondData10
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_secondData10
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: 0.7118
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 3.8835 | 1.33 | 10 | 3.4352 |
| 2.9529 | 2.67 | 20 | 2.3780 |
| 1.991 | 4.0 | 30 | 1.6911 |
| 1.5061 | 5.33 | 40 | 1.2670 |
| 1.0666 | 6.67 | 50 | 0.8670 |
| 0.8464 | 8.0 | 60 | 0.8088 |
| 0.7622 | 9.33 | 70 | 0.7478 |
| 0.6869 | 10.67 | 80 | 0.7055 |
| 0.6336 | 12.0 | 90 | 0.6840 |
| 0.5789 | 13.33 | 100 | 0.6749 |
| 0.5518 | 14.67 | 110 | 0.6685 |
| 0.5159 | 16.0 | 120 | 0.6657 |
| 0.4894 | 17.33 | 130 | 0.6743 |
| 0.4674 | 18.67 | 140 | 0.6720 |
| 0.4496 | 20.0 | 150 | 0.6806 |
| 0.4292 | 21.33 | 160 | 0.6883 |
| 0.421 | 22.67 | 170 | 0.6910 |
| 0.4088 | 24.0 | 180 | 0.6956 |
| 0.3988 | 25.33 | 190 | 0.7014 |
| 0.3898 | 26.67 | 200 | 0.7065 |
| 0.3827 | 28.0 | 210 | 0.7091 |
| 0.3819 | 29.33 | 220 | 0.7104 |
| 0.3778 | 30.67 | 230 | 0.7117 |
| 0.3803 | 32.0 | 240 | 0.7126 |
| 0.3804 | 33.33 | 250 | 0.7118 |
### Framework versions
- PEFT 0.4.0
- Transformers 4.38.2
- Pytorch 2.4.0+cu121
- Datasets 2.13.1
- Tokenizers 0.15.2
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