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README.md
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---
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library_name: peft
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license: llama3.2
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base_model: meta-llama/Llama-3.2-3B-Instruct
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tags:
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- trl
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- sft
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- generated_from_trainer
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model-index:
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- name: Llama-3.2-3B-Instruct-combinedTask-extraData
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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-3.2-3B-Instruct-combinedTask-extraData
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This model is a fine-tuned version of [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1110
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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: 1e-05
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- train_batch_size: 1
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- eval_batch_size: 1
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- seed: 42
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- gradient_accumulation_steps: 5
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- total_train_batch_size: 5
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- optimizer: Use paged_adamw_32bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.01
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- num_epochs: 1
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- mixed_precision_training: Native AMP
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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 | 0 | 1.9377 |
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| 0.9095 | 0.0937 | 100 | 0.1349 |
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| 0.6606 | 0.1873 | 200 | 0.1242 |
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| 0.6203 | 0.2810 | 300 | 0.1202 |
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| 0.381 | 0.3746 | 400 | 0.1173 |
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| 0.4891 | 0.4683 | 500 | 0.1152 |
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| 0.6971 | 0.5619 | 600 | 0.1139 |
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| 0.4967 | 0.6556 | 700 | 0.1127 |
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| 0.4527 | 0.7492 | 800 | 0.1118 |
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| 0.4013 | 0.8429 | 900 | 0.1114 |
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| 0.4653 | 0.9365 | 1000 | 0.1110 |
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### Framework versions
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- PEFT 0.13.2
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- Transformers 4.46.0.dev0
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- Pytorch 2.2.0
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- Datasets 3.0.2
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- Tokenizers 0.20.1
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