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README.md
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---
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library_name: peft
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license: apache-2.0
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base_model: EleutherAI/pythia-410m-deduped
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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: eecb421a-3b79-4353-97c2-0fa385ded337
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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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# eecb421a-3b79-4353-97c2-0fa385ded337
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This model is a fine-tuned version of [EleutherAI/pythia-410m-deduped](https://huggingface.co/EleutherAI/pythia-410m-deduped) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.8016
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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: 0.000215
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 150
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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 | 0.0009 | 1 | 4.0474 |
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| 6.4608 | 0.0432 | 50 | 3.1346 |
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| 6.6264 | 0.0864 | 100 | 3.3024 |
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| 6.255 | 0.1295 | 150 | 3.1822 |
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| 6.8375 | 0.1727 | 200 | 3.0047 |
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| 6.1797 | 0.2159 | 250 | 2.9974 |
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| 6.1913 | 0.2591 | 300 | 2.8754 |
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| 5.8536 | 0.3022 | 350 | 2.9318 |
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| 6.0825 | 0.3454 | 400 | 2.8580 |
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| 6.3589 | 0.3886 | 450 | 2.7873 |
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| 5.9893 | 0.4318 | 500 | 2.8016 |
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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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