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README.md
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---
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library_name: peft
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license: mit
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base_model: numind/NuExtract-v1.5
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tags:
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- axolotl
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- generated_from_trainer
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model-index:
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- name: d1f061a1-d2f7-49d3-b213-76afe262c4e0
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
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<br>
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# d1f061a1-d2f7-49d3-b213-76afe262c4e0
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This model is a fine-tuned version of [numind/NuExtract-v1.5](https://huggingface.co/numind/NuExtract-v1.5) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.7836
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.000206
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 8
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- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 50
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- training_steps: 500
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| No log | 0.0001 | 1 | 1.9060 |
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| 4.0029 | 0.0062 | 50 | 1.8319 |
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| 3.7965 | 0.0124 | 100 | 1.8216 |
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| 3.9925 | 0.0186 | 150 | 1.8100 |
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| 3.8813 | 0.0248 | 200 | 1.8056 |
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| 3.956 | 0.0309 | 250 | 1.8006 |
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| 3.9035 | 0.0371 | 300 | 1.7916 |
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| 3.9251 | 0.0433 | 350 | 1.7878 |
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| 3.7906 | 0.0495 | 400 | 1.7845 |
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| 3.8648 | 0.0557 | 450 | 1.7834 |
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| 3.8805 | 0.0619 | 500 | 1.7836 |
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### Framework versions
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- PEFT 0.13.2
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- Transformers 4.46.0
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- Pytorch 2.5.0+cu124
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- Datasets 3.0.1
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- Tokenizers 0.20.1
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