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README.md ADDED
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+ ---
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+ base_model: microsoft/Phi-3.5-mini-instruct
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+ library_name: peft
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+ license: mit
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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: Phi-3.5-MultiCap-tool-new
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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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+ # Phi-3.5-MultiCap-tool-new
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+
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+ This model is a fine-tuned version of [microsoft/Phi-3.5-mini-instruct](https://huggingface.co/microsoft/Phi-3.5-mini-instruct) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4307
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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: 0.0001
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - gradient_accumulation_steps: 8
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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: linear
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+ - lr_scheduler_warmup_ratio: 0.03
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+ - num_epochs: 2
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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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+ | 0.6201 | 0.2256 | 50 | 0.6052 |
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+ | 0.4722 | 0.4512 | 100 | 0.4734 |
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+ | 0.4609 | 0.6768 | 150 | 0.4540 |
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+ | 0.4803 | 0.9024 | 200 | 0.4442 |
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+ | 0.4207 | 1.1280 | 250 | 0.4381 |
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+ | 0.4162 | 1.3536 | 300 | 0.4343 |
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+ | 0.3933 | 1.5792 | 350 | 0.4320 |
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+ | 0.4517 | 1.8049 | 400 | 0.4307 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.12.0
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+ - Transformers 4.44.2
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+ - Pytorch 2.4.1+cu124
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+ - Datasets 3.0.0
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+ - Tokenizers 0.19.1
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