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--- |
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base_model: barc0/cot-transduction-arc-heavy |
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datasets: |
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- barc0/cot_train_dataset_960_ms10_v2 |
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- barc0/cot_rearc_dataset_100_ms10 |
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- barc0/seeds_cot |
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library_name: peft |
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license: llama3.1 |
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tags: |
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- alignment-handbook |
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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: cot-trainset-ft-transduction-v3-lora-train |
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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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# cot-trainset-ft-transduction-v3-lora-train |
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This model is a fine-tuned version of [barc0/cot-transduction-arc-heavy](https://huggingface.co/barc0/cot-transduction-arc-heavy) on the barc0/cot_train_dataset_960_ms10_v2, the barc0/cot_rearc_dataset_100_ms10 and the barc0/seeds_cot datasets. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1921 |
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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: 2 |
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- eval_batch_size: 2 |
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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: 16 |
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- total_eval_batch_size: 8 |
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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_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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| 0.1018 | 0.9982 | 277 | 0.1238 | |
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| 0.0822 | 1.9964 | 554 | 0.1333 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.45.0.dev0 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
