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license: mit |
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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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# MirrorAPI |
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This model is a fine-tuned version of [Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) |
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### Training and evaluation data |
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The training data of MirrorAPI consists of: |
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- [`train_sft.json`](https://huggingface.co/datasets/stabletoolbench/MirrorAPI/blob/main/train/train_sft.json) |
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- [`train_cot.json`](https://huggingface.co/datasets/stabletoolbench/MirrorAPI/blob/main/train/train_cot.json) |
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- [`train_augment.json`](https://huggingface.co/datasets/stabletoolbench/MirrorAPI/blob/main/train/train_augment.json) |
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The testing data are under [`test_sft`](https://huggingface.co/datasets/stabletoolbench/MirrorAPI/tree/main/test/test_sft) and [`test_cot`](https://huggingface.co/datasets/stabletoolbench/MirrorAPI/tree/main/test/test_cot) for SFT and CoT modes, respectively. |
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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: 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: 8 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 16 |
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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: 0.04 |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 5.0 |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu118 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
