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llama3-section-classifier-2ksamples-10epochs
dklpp/llama3-section-classifier-2ksamples-10epochs
llama3-section-classifier-2ksamples-10epochs is a machine learning model from dklpp. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as llama3.1.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- llama3.1
- Access
- Public
- Created
- Nov 11, 2025
- Updated
- Nov 11, 2025
- SHA
- 83b81045
Base models
Model card
From the Hugging Face model README
<!-- 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-section-classifier-10ksamples-1epoch
This model is a fine-tuned version of meta-llama/Llama-3.1-8B-Instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9118
- Accuracy: 0.6895
- Precision: 0.6843
- Recall: 0.6895
- F1: 0.6845
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: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 7.2784 | 1.0 | 3094 | 0.9118 | 0.6895 | 0.6843 | 0.6895 | 0.6845 |
Framework versions
- PEFT 0.17.1
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
- Library
- peft
- License
- llama3.1
- Created
- Nov 11, 2025
- Updated
- Nov 11, 2025