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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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<!-- 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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# cls_alldata_phi3_v1 |
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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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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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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### Training results |
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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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### Framework versions |
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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 |
