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---
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 |