Model save
Browse files- README.md +68 -0
- all_results.json +9 -0
- train_results.json +9 -0
- trainer_state.json +0 -0
README.md
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---
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base_model: barc0/Llama-3.1-ARC-Heavy-Transduction-8B
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library_name: peft
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license: llama3.1
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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: arc-heavy-llama3.1-8b-lora64-testtime-finetuning
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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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# arc-heavy-llama3.1-8b-lora64-testtime-finetuning
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This model is a fine-tuned version of [barc0/Llama-3.1-ARC-Heavy-Transduction-8B](https://huggingface.co/barc0/Llama-3.1-ARC-Heavy-Transduction-8B) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0550
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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: 0.0002
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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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- distributed_type: multi-GPU
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- num_devices: 4
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 32
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- total_eval_batch_size: 16
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- optimizer: Use 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
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 0.0373 | 1.0 | 667 | 0.0589 |
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| 0.0344 | 2.0 | 1334 | 0.0550 |
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### Framework versions
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- PEFT 0.13.2
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- Transformers 4.46.2
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- Pytorch 2.4.0+cu121
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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all_results.json
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{
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"epoch": 2.0,
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"total_flos": 2659138639233024.0,
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"train_loss": 0.03610908869839646,
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"train_runtime": 12784.2292,
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"train_samples": 21343,
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"train_samples_per_second": 3.339,
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"train_steps_per_second": 0.104
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}
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train_results.json
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{
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"epoch": 2.0,
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"total_flos": 2659138639233024.0,
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"train_loss": 0.03610908869839646,
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"train_runtime": 12784.2292,
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"train_samples": 21343,
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"train_samples_per_second": 3.339,
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"train_steps_per_second": 0.104
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}
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trainer_state.json
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