---
library_name: peft
license: llama2
base_model: meta-llama/Llama-2-7b-chat-hf
tags:
- generated_from_trainer
model-index:
- name: Llama2-Instruct-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. -->

# Llama2-Instruct-7B

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: 0.2191

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.063         | 0.1144 | 50   | 1.8637          |
| 1.3888        | 0.2288 | 100  | 0.8130          |
| 0.4576        | 0.3432 | 150  | 0.3154          |
| 0.3002        | 0.4577 | 200  | 0.2924          |
| 0.285         | 0.5721 | 250  | 0.2795          |
| 0.2711        | 0.6865 | 300  | 0.2652          |
| 0.2598        | 0.8009 | 350  | 0.2550          |
| 0.2469        | 0.9153 | 400  | 0.2471          |
| 0.2427        | 1.0297 | 450  | 0.2420          |
| 0.239         | 1.1442 | 500  | 0.2386          |
| 0.2361        | 1.2586 | 550  | 0.2361          |
| 0.2332        | 1.3730 | 600  | 0.2345          |
| 0.2308        | 1.4874 | 650  | 0.2324          |
| 0.2301        | 1.6018 | 700  | 0.2307          |
| 0.228         | 1.7162 | 750  | 0.2295          |
| 0.228         | 1.8307 | 800  | 0.2285          |
| 0.2277        | 1.9451 | 850  | 0.2276          |
| 0.2257        | 2.0595 | 900  | 0.2269          |
| 0.2251        | 2.1739 | 950  | 0.2259          |
| 0.223         | 2.2883 | 1000 | 0.2248          |
| 0.2236        | 2.4027 | 1050 | 0.2241          |
| 0.221         | 2.5172 | 1100 | 0.2234          |
| 0.2211        | 2.6316 | 1150 | 0.2234          |
| 0.2214        | 2.7460 | 1200 | 0.2224          |
| 0.2205        | 2.8604 | 1250 | 0.2219          |
| 0.2199        | 2.9748 | 1300 | 0.2214          |
| 0.2193        | 3.0892 | 1350 | 0.2210          |
| 0.219         | 3.2037 | 1400 | 0.2206          |
| 0.2191        | 3.3181 | 1450 | 0.2203          |
| 0.2185        | 3.4325 | 1500 | 0.2198          |
| 0.2169        | 3.5469 | 1550 | 0.2197          |
| 0.2176        | 3.6613 | 1600 | 0.2194          |
| 0.2171        | 3.7757 | 1650 | 0.2192          |
| 0.2148        | 3.8902 | 1700 | 0.2191          |


### Framework versions

- PEFT 0.14.0
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1