61 lines
2.7 KiB
Markdown
61 lines
2.7 KiB
Markdown
---
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library_name: transformers
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base_model: adpretko/x86-to-llvm-o2_epoch2
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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: x86-to-llvm-o2_epoch3-AMD
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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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# x86-to-llvm-o2_epoch3-AMD
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This model is a fine-tuned version of [adpretko/x86-to-llvm-o2_epoch2](https://huggingface.co/adpretko/x86-to-llvm-o2_epoch2) on the x86-to-llvm-o2_part_00, the x86-to-llvm-o2_part_01, the x86-to-llvm-o2_part_02, the x86-to-llvm-o2_part_03, the x86-to-llvm-o2_part_04, the x86-to-llvm-o2_part_05, the x86-to-llvm-o2_part_06, the x86-to-llvm-o2_part_07, the x86-to-llvm-o2_part_08, the x86-to-llvm-o2_part_09, the x86-to-llvm-o2_part_10, the x86-to-llvm-o2_part_11, the x86-to-llvm-o2_part_12, the x86-to-llvm-o2_part_13, the x86-to-llvm-o2_part_14, the x86-to-llvm-o2_part_15, the x86-to-llvm-o2_part_16, the x86-to-llvm-o2_part_17, the x86-to-llvm-o2_part_18, the x86-to-llvm-o2_part_19, the x86-to-llvm-o2_part_20, the x86-to-llvm-o2_part_21, the x86-to-llvm-o2_part_22, the x86-to-llvm-o2_part_23, the x86-to-llvm-o2_part_24, the x86-to-llvm-o2_part_25, the x86-to-llvm-o2_part_26, the x86-to-llvm-o2_part_27, the x86-to-llvm-o2_part_28, the x86-to-llvm-o2_part_29, the x86-to-llvm-o2_part_30, the x86-to-llvm-o2_part_31, the x86-to-llvm-o2_part_32, the x86-to-llvm-o2_part_33, the x86-to-llvm-o2_part_34, the x86-to-llvm-o2_part_35, the x86-to-llvm-o2_part_36, the x86-to-llvm-o2_part_37, the x86-to-llvm-o2_part_38, the x86-to-llvm-o2_part_39, the x86-to-llvm-o2_part_40, the x86-to-llvm-o2_part_41, the x86-to-llvm-o2_part_42, the x86-to-llvm-o2_part_43, the x86-to-llvm-o2_part_44, the x86-to-llvm-o2_part_45, the x86-to-llvm-o2_part_46, the x86-to-llvm-o2_part_47 and the x86-to-llvm-o2_part_48 datasets.
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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: 8
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- eval_batch_size: 8
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 8
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 512
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- total_eval_batch_size: 64
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 1.0
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### Training results
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### Framework versions
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- Transformers 4.55.0
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- Pytorch 2.8.0+rocm6.3
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- Datasets 3.6.0
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- Tokenizers 0.21.1
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