dklpp
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llama3_ft_section_classifier

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 ---
-base_model: meta-llama/Llama-3.1-8B-Instruct
 library_name: peft
 tags:
 - base_model:adapter:meta-llama/Llama-3.1-8B-Instruct
 - lora
 - transformers
 ---
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 ### Framework versions
-- PEFT 0.17.1

 ---
 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