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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: d4c496cd-fce4-4e40-bf9e-4bdcedcbe341
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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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# d4c496cd-fce4-4e40-bf9e-4bdcedcbe341
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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: 3.1905
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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: 0.00021
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 100
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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 | 4.0563 |
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| 8.7892 | 0.0432 | 50 | 5.3484 |
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| 9.2869 | 0.0864 | 100 | 4.1115 |
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| 9.8128 | 0.1295 | 150 | 4.5094 |
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| 6.9788 | 0.1727 | 200 | 3.5344 |
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| 6.71 | 0.2159 | 250 | 3.5054 |
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| 6.7211 | 0.2591 | 300 | 3.3468 |
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| 6.9331 | 0.3022 | 350 | 3.2757 |
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| 6.4847 | 0.3454 | 400 | 3.2017 |
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| 6.6208 | 0.3886 | 450 | 3.2093 |
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| 6.4061 | 0.4318 | 500 | 3.1905 |
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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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