Добавление обновлённого README.md без блоков <details>
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README.md
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---
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library_name: peft
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base_model: katuni4ka/tiny-random-falcon-40b
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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: 0b6ca836-a2a2-412d-825a-f90dbab4d025
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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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# 0b6ca836-a2a2-412d-825a-f90dbab4d025
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This model is a fine-tuned version of [katuni4ka/tiny-random-falcon-40b](https://huggingface.co/katuni4ka/tiny-random-falcon-40b) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 10.7366
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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: 0.000202
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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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: constant
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- lr_scheduler_warmup_steps: 50
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- training_steps: 400
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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 | 0.0016 | 1 | 11.1054 |
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| 43.6621 | 0.0793 | 50 | 10.8431 |
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| 43.3102 | 0.1587 | 100 | 10.8165 |
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| 43.237 | 0.2380 | 150 | 10.7994 |
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| 43.1916 | 0.3173 | 200 | 10.7873 |
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| 43.1396 | 0.3967 | 250 | 10.7763 |
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| 43.1061 | 0.4760 | 300 | 10.7662 |
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| 43.0448 | 0.5553 | 350 | 10.7555 |
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| 42.9742 | 0.6347 | 400 | 10.7366 |
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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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