67 lines
1.7 KiB
Markdown
67 lines
1.7 KiB
Markdown
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---
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library_name: transformers
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license: other
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base_model: LLM-Research/Llama-3.2-3B-Instruct
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tags:
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- llama-factory
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- full
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- generated_from_trainer
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model-index:
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- name: llama3_3b_instruct_vallina_full_sft_30k
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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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# llama3_3b_instruct_vallina_full_sft_30k
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This model is a fine-tuned version of [LLM-Research/Llama-3.2-3B-Instruct](https://huggingface.co/LLM-Research/Llama-3.2-3B-Instruct) on the deepmath_plain_30k_train dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4737
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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: 2e-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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- distributed_type: multi-GPU
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- num_devices: 2
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 16
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- total_eval_batch_size: 2
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- optimizer: Use OptimizerNames.ADAMW_TORCH 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_ratio: 0.1
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- num_epochs: 2.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 0.3879 | 1.7182 | 1000 | 0.4751 |
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### Framework versions
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- Transformers 4.52.4
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- Pytorch 2.6.0+cu124
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- Datasets 3.6.0
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- Tokenizers 0.21.1
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