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End of training
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README.md
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---
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base_model: meta-llama/Llama-3.2-1B
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library_name: peft
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license: llama3.2
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tags:
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- generated_from_trainer
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model-index:
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- name: Llama-3.2-1B
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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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# Llama-3.2-1B
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This model is a fine-tuned version of [meta-llama/Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2404
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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: 0.0005
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 30
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- training_steps: 2000
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 0.4565 | 0.05 | 100 | 0.4042 |
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| 0.355 | 0.1 | 200 | 0.3224 |
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| 0.3004 | 0.15 | 300 | 0.3054 |
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| 0.2844 | 0.2 | 400 | 0.2904 |
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| 0.2331 | 0.25 | 500 | 0.2829 |
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| 0.241 | 0.3 | 600 | 0.2737 |
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| 0.3013 | 0.35 | 700 | 0.2682 |
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| 0.2619 | 0.4 | 800 | 0.2626 |
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| 0.2367 | 0.45 | 900 | 0.2588 |
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| 0.2152 | 0.5 | 1000 | 0.2563 |
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| 0.2464 | 0.55 | 1100 | 0.2521 |
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| 0.2443 | 0.6 | 1200 | 0.2491 |
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| 0.2639 | 0.65 | 1300 | 0.2467 |
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| 0.2602 | 0.7 | 1400 | 0.2447 |
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| 0.291 | 0.75 | 1500 | 0.2434 |
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| 0.2524 | 0.8 | 1600 | 0.2419 |
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| 0.272 | 0.85 | 1700 | 0.2410 |
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| 0.2273 | 0.9 | 1800 | 0.2406 |
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| 0.2584 | 0.95 | 1900 | 0.2405 |
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| 0.237 | 1.0 | 2000 | 0.2404 |
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### Framework versions
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- PEFT 0.13.0
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- Transformers 4.44.2
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- Pytorch 2.4.1+cu121
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- Datasets 3.0.1
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- Tokenizers 0.19.1
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