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README.md ADDED
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+ ---
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+ library_name: peft
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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: phi2-mentalchat16k
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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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+ # phi2-mentalchat16k
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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 the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7296
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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: 0.0002
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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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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 8
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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: 0.03
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+ - num_epochs: 4
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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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+ | 0.8915 | 0.1496 | 100 | 0.8518 |
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+ | 0.8464 | 0.2992 | 200 | 0.8102 |
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+ | 0.7874 | 0.4488 | 300 | 0.7927 |
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+ | 0.7999 | 0.5984 | 400 | 0.7814 |
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+ | 0.7901 | 0.7479 | 500 | 0.7731 |
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+ | 0.7801 | 0.8975 | 600 | 0.7647 |
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+ | 0.7585 | 1.0471 | 700 | 0.7639 |
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+ | 0.7592 | 1.1967 | 800 | 0.7576 |
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+ | 0.7431 | 1.3463 | 900 | 0.7542 |
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+ | 0.7555 | 1.4959 | 1000 | 0.7501 |
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+ | 0.7354 | 1.6455 | 1100 | 0.7456 |
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+ | 0.7281 | 1.7951 | 1200 | 0.7422 |
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+ | 0.7312 | 1.9447 | 1300 | 0.7395 |
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+ | 0.6984 | 2.0942 | 1400 | 0.7389 |
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+ | 0.7037 | 2.2438 | 1500 | 0.7382 |
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+ | 0.6913 | 2.3934 | 1600 | 0.7357 |
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+ | 0.7229 | 2.5430 | 1700 | 0.7341 |
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+ | 0.7095 | 2.6926 | 1800 | 0.7326 |
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+ | 0.6994 | 2.8422 | 1900 | 0.7319 |
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+ | 0.6995 | 2.9918 | 2000 | 0.7298 |
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+ | 0.6887 | 3.1414 | 2100 | 0.7314 |
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+ | 0.6712 | 3.2909 | 2200 | 0.7308 |
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+ | 0.6867 | 3.4405 | 2300 | 0.7300 |
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+ | 0.6817 | 3.5901 | 2400 | 0.7299 |
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+ | 0.681 | 3.7397 | 2500 | 0.7296 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.13.2
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+ - Transformers 4.46.3
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+ - Pytorch 2.4.1+cu118
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+ - Datasets 3.1.0
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+ - Tokenizers 0.20.3
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