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---
base_model: NousResearch/Llama-2-7b-hf
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Cold-Data-LLama-2-7B
results: []
---
<!-- 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. -->
# Cold-Data-LLama-2-7B
This model is a fine-tuned version of [NousResearch/Llama-2-7b-hf](https://huggingface.co/NousResearch/Llama-2-7b-hf) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0526
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.002
- train_batch_size: 16
- eval_batch_size: 32
- 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: linear
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.1019 | 1.992 | 249 | 0.1022 |
| 0.0542 | 3.984 | 498 | 0.0540 |
| 0.0508 | 5.976 | 747 | 0.0513 |
| 0.0479 | 7.968 | 996 | 0.0515 |
| 0.0472 | 9.96 | 1245 | 0.0537 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.43.3
- Pytorch 2.3.1+cu121
- Datasets 2.17.0
- Tokenizers 0.19.1