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---
library_name: peft
license: llama3.1
base_model: meta-llama/Llama-3.1-8B-Instruct
tags:
- base_model:adapter:meta-llama/Llama-3.1-8B-Instruct
- lora
- transformers
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: llama3_ft_section_classifier
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. -->
# llama3_ft_section_classifier
This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3342
- Accuracy: 0.6232
- Precision: 0.6126
- Recall: 0.6232
- F1: 0.6164
## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 16.483 | 1.0 | 275 | 1.3758 | 0.5423 | 0.5769 | 0.5423 | 0.5311 |
| 9.7264 | 2.0 | 550 | 1.1577 | 0.6095 | 0.6215 | 0.6095 | 0.6065 |
| 8.2372 | 3.0 | 825 | 1.1713 | 0.6041 | 0.6264 | 0.6041 | 0.6061 |
| 6.1069 | 4.0 | 1100 | 1.2993 | 0.6123 | 0.6090 | 0.6123 | 0.6025 |
| 3.1467 | 5.0 | 1375 | 1.5804 | 0.6027 | 0.6255 | 0.6027 | 0.6085 |
| 1.3995 | 6.0 | 1650 | 1.9973 | 0.6077 | 0.6005 | 0.6077 | 0.5994 |
| 0.8489 | 7.0 | 1925 | 2.3380 | 0.6082 | 0.6070 | 0.6082 | 0.5990 |
| 0.4705 | 8.0 | 2200 | 2.5919 | 0.6245 | 0.6223 | 0.6245 | 0.6172 |
| 0.186 | 9.0 | 2475 | 2.8240 | 0.6223 | 0.6275 | 0.6223 | 0.6238 |
| 0.0636 | 10.0 | 2750 | 3.0796 | 0.6209 | 0.6273 | 0.6209 | 0.6190 |
| 0.0248 | 11.0 | 3025 | 3.2076 | 0.6259 | 0.6269 | 0.6259 | 0.6231 |
| 0.0009 | 12.0 | 3300 | 3.2148 | 0.6214 | 0.6133 | 0.6214 | 0.6158 |
| 0.0001 | 13.0 | 3575 | 3.2700 | 0.6209 | 0.6132 | 0.6209 | 0.6158 |
| 0.0 | 14.0 | 3850 | 3.2962 | 0.6223 | 0.6124 | 0.6223 | 0.6158 |
| 0.0 | 15.0 | 4125 | 3.3102 | 0.6223 | 0.6118 | 0.6223 | 0.6156 |
| 0.0 | 16.0 | 4400 | 3.3219 | 0.6236 | 0.6138 | 0.6236 | 0.6173 |
| 0.0 | 17.0 | 4675 | 3.3271 | 0.6232 | 0.6125 | 0.6232 | 0.6162 |
| 0.0 | 18.0 | 4950 | 3.3285 | 0.6218 | 0.6108 | 0.6218 | 0.6148 |
| 0.0 | 19.0 | 5225 | 3.3359 | 0.6232 | 0.6126 | 0.6232 | 0.6163 |
| 0.0 | 20.0 | 5500 | 3.3342 | 0.6232 | 0.6126 | 0.6232 | 0.6164 |
### Framework versions
- PEFT 0.17.1
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1 |