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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-Instruct
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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-Instruct_v2
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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-Instruct_v2
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This model is a fine-tuned version of [meta-llama/Llama-3.2-1B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2356
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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: 4
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- eval_batch_size: 4
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 16
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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: 3000
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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 | 0.0333 | 100 | 0.4058 |
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| 0.3313 | 0.0667 | 200 | 0.3428 |
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| 0.3139 | 0.1 | 300 | 0.3192 |
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| 0.2903 | 0.1333 | 400 | 0.3034 |
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| 0.2639 | 0.1667 | 500 | 0.2944 |
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| 0.2688 | 0.2 | 600 | 0.2869 |
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| 0.3097 | 0.2333 | 700 | 0.2791 |
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| 0.2462 | 0.2667 | 800 | 0.2735 |
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| 0.3257 | 0.3 | 900 | 0.2684 |
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| 0.2738 | 0.3333 | 1000 | 0.2638 |
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| 0.2572 | 0.3667 | 1100 | 0.2598 |
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| 0.234 | 0.4 | 1200 | 0.2566 |
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| 0.2233 | 0.4333 | 1300 | 0.2537 |
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| 0.2996 | 0.4667 | 1400 | 0.2515 |
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| 0.2178 | 0.5 | 1500 | 0.2490 |
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| 0.2251 | 0.5333 | 1600 | 0.2470 |
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| 0.262 | 0.5667 | 1700 | 0.2450 |
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| 0.2683 | 0.6 | 1800 | 0.2430 |
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| 0.1966 | 0.6333 | 1900 | 0.2416 |
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| 0.2451 | 0.6667 | 2000 | 0.2403 |
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| 0.2247 | 0.7 | 2100 | 0.2393 |
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| 0.1865 | 0.7333 | 2200 | 0.2384 |
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| 0.2837 | 0.7667 | 2300 | 0.2378 |
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| 0.2312 | 0.8 | 2400 | 0.2371 |
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| 0.239 | 0.8333 | 2500 | 0.2365 |
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| 0.2064 | 0.8667 | 2600 | 0.2362 |
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| 0.208 | 0.9 | 2700 | 0.2358 |
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| 0.2588 | 0.9333 | 2800 | 0.2356 |
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| 0.2029 | 0.9667 | 2900 | 0.2356 |
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| 0.2404 | 1.0 | 3000 | 0.2356 |
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### Framework versions
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- PEFT 0.13.2
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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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