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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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- generated_from_trainer |
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base_model: microsoft/Phi-3-mini-128k-instruct |
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model-index: |
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- name: working |
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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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# working |
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This model is a fine-tuned version of [microsoft/Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4364 |
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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: 6 |
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- eval_batch_size: 6 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 24 |
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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_steps: 2 |
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- num_epochs: 30 |
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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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| 2.8501 | 1.0 | 3 | 2.2605 | |
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| 2.1387 | 2.0 | 6 | 1.7344 | |
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| 1.5826 | 3.0 | 9 | 1.3666 | |
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| 1.2187 | 4.0 | 12 | 1.0485 | |
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| 0.8879 | 5.0 | 15 | 0.7558 | |
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| 0.6134 | 6.0 | 18 | 0.5396 | |
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| 0.4343 | 7.0 | 21 | 0.4304 | |
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| 0.3557 | 8.0 | 24 | 0.3943 | |
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| 0.3205 | 9.0 | 27 | 0.3689 | |
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| 0.2947 | 10.0 | 30 | 0.3580 | |
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| 0.2727 | 11.0 | 33 | 0.3371 | |
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| 0.2506 | 12.0 | 36 | 0.3361 | |
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| 0.2291 | 13.0 | 39 | 0.3342 | |
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| 0.2098 | 14.0 | 42 | 0.3332 | |
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| 0.1911 | 15.0 | 45 | 0.3446 | |
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| 0.1761 | 16.0 | 48 | 0.3334 | |
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| 0.159 | 17.0 | 51 | 0.3453 | |
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| 0.1399 | 18.0 | 54 | 0.3540 | |
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| 0.124 | 19.0 | 57 | 0.3631 | |
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| 0.1123 | 20.0 | 60 | 0.3636 | |
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| 0.0992 | 21.0 | 63 | 0.3778 | |
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| 0.0862 | 22.0 | 66 | 0.3862 | |
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| 0.0783 | 23.0 | 69 | 0.3966 | |
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| 0.0704 | 24.0 | 72 | 0.4072 | |
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| 0.0627 | 25.0 | 75 | 0.4178 | |
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| 0.0582 | 26.0 | 78 | 0.4200 | |
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| 0.0553 | 27.0 | 81 | 0.4283 | |
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| 0.0521 | 28.0 | 84 | 0.4338 | |
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| 0.0505 | 29.0 | 87 | 0.4366 | |
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| 0.0494 | 30.0 | 90 | 0.4364 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
