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cls_alldata_phi3_v1

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sft
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+ ---
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+ license: mit
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+ library_name: peft
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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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+ base_model: microsoft/Phi-3-mini-4k-instruct
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+ datasets:
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+ - generator
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+ model-index:
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+ - name: cls_alldata_phi3_v1
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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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+ # cls_alldata_phi3_v1
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+
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+ This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on the generator dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4956
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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: 2
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_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: constant
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+ - lr_scheduler_warmup_ratio: 0.03
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+ - num_epochs: 2
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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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+ | 0.7566 | 0.0559 | 20 | 0.7643 |
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+ | 0.6863 | 0.1117 | 40 | 0.7089 |
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+ | 0.6538 | 0.1676 | 60 | 0.6706 |
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+ | 0.6261 | 0.2235 | 80 | 0.6499 |
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+ | 0.6402 | 0.2793 | 100 | 0.6321 |
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+ | 0.594 | 0.3352 | 120 | 0.6226 |
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+ | 0.5956 | 0.3911 | 140 | 0.6121 |
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+ | 0.5743 | 0.4469 | 160 | 0.6016 |
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+ | 0.5494 | 0.5028 | 180 | 0.5903 |
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+ | 0.5861 | 0.5587 | 200 | 0.5887 |
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+ | 0.5431 | 0.6145 | 220 | 0.5801 |
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+ | 0.5404 | 0.6704 | 240 | 0.5746 |
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+ | 0.5401 | 0.7263 | 260 | 0.5695 |
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+ | 0.5363 | 0.7821 | 280 | 0.5644 |
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+ | 0.5534 | 0.8380 | 300 | 0.5608 |
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+ | 0.5936 | 0.8939 | 320 | 0.5552 |
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+ | 0.5139 | 0.9497 | 340 | 0.5496 |
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+ | 0.5096 | 1.0056 | 360 | 0.5468 |
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+ | 0.4891 | 1.0615 | 380 | 0.5468 |
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+ | 0.4524 | 1.1173 | 400 | 0.5433 |
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+ | 0.4568 | 1.1732 | 420 | 0.5397 |
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+ | 0.4462 | 1.2291 | 440 | 0.5374 |
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+ | 0.4605 | 1.2849 | 460 | 0.5337 |
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+ | 0.4469 | 1.3408 | 480 | 0.5328 |
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+ | 0.458 | 1.3966 | 500 | 0.5313 |
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+ | 0.4378 | 1.4525 | 520 | 0.5250 |
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+ | 0.4654 | 1.5084 | 540 | 0.5232 |
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+ | 0.4563 | 1.5642 | 560 | 0.5200 |
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+ | 0.4664 | 1.6201 | 580 | 0.5155 |
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+ | 0.4308 | 1.6760 | 600 | 0.5128 |
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+ | 0.443 | 1.7318 | 620 | 0.5082 |
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+ | 0.4508 | 1.7877 | 640 | 0.5070 |
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+ | 0.4511 | 1.8436 | 660 | 0.4999 |
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+ | 0.4467 | 1.8994 | 680 | 0.4996 |
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+ | 0.4723 | 1.9553 | 700 | 0.4956 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.11.1
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+ - Transformers 4.41.1
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1