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V0507HMA15HV3

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  1. README.md +93 -0
  2. adapter_config.json +50 -0
  3. adapter_model.bin +3 -0
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  10. vocab.json +0 -0
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+ ---
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+ license: mit
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+ base_model: microsoft/phi-2
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: V0507HMA15HV3
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+ results: []
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+ ---
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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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+
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+ # V0507HMA15HV3
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+
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+ This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0511
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0003
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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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+ - gradient_accumulation_steps: 16
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+ - total_train_batch_size: 128
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine_with_restarts
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+ - lr_scheduler_warmup_steps: 100
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+ - num_epochs: 3
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | 1.9302 | 0.09 | 10 | 0.6932 |
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+ | 0.2793 | 0.18 | 20 | 0.1168 |
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+ | 0.1139 | 0.27 | 30 | 0.0926 |
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+ | 0.0965 | 0.36 | 40 | 0.0849 |
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+ | 0.0863 | 0.45 | 50 | 0.0783 |
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+ | 0.0925 | 0.54 | 60 | 0.0724 |
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+ | 0.0781 | 0.63 | 70 | 0.0691 |
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+ | 0.0773 | 0.73 | 80 | 0.0701 |
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+ | 0.077 | 0.82 | 90 | 0.0726 |
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+ | 0.0778 | 0.91 | 100 | 0.0682 |
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+ | 0.0767 | 1.0 | 110 | 0.0652 |
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+ | 0.0604 | 1.09 | 120 | 0.0701 |
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+ | 0.0669 | 1.18 | 130 | 0.0701 |
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+ | 0.0642 | 1.27 | 140 | 0.0682 |
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+ | 0.0648 | 1.36 | 150 | 0.0742 |
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+ | 0.0722 | 1.45 | 160 | 0.0779 |
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+ | 0.0734 | 1.54 | 170 | 0.0690 |
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+ | 0.0741 | 1.63 | 180 | 0.0717 |
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+ | 0.0708 | 1.72 | 190 | 0.0667 |
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+ | 0.0713 | 1.81 | 200 | 0.0723 |
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+ | 0.0594 | 1.9 | 210 | 0.0629 |
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+ | 0.0572 | 1.99 | 220 | 0.0589 |
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+ | 0.0405 | 2.08 | 230 | 0.0625 |
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+ | 0.0339 | 2.18 | 240 | 0.0483 |
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+ | 0.0298 | 2.27 | 250 | 0.0565 |
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+ | 0.022 | 2.36 | 260 | 0.0620 |
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+ | 0.025 | 2.45 | 270 | 0.0513 |
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+ | 0.0259 | 2.54 | 280 | 0.0502 |
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+ | 0.0236 | 2.63 | 290 | 0.0509 |
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+ | 0.0207 | 2.72 | 300 | 0.0506 |
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+ | 0.027 | 2.81 | 310 | 0.0511 |
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+ | 0.0237 | 2.9 | 320 | 0.0511 |
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+ | 0.0238 | 2.99 | 330 | 0.0511 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.0.dev0
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+ - Pytorch 2.1.2+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.14.1
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