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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-6 |
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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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# Phi-3.5-MultiCap-6 |
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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: 0.5045 |
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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: 0.0001 |
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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: 6 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.9384 | 0.2256 | 50 | 0.9431 | |
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| 0.6189 | 0.4512 | 100 | 0.6235 | |
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| 0.5667 | 0.6768 | 150 | 0.5738 | |
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| 0.6109 | 0.9024 | 200 | 0.5533 | |
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| 0.537 | 1.1280 | 250 | 0.5418 | |
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| 0.5254 | 1.3536 | 300 | 0.5341 | |
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| 0.495 | 1.5792 | 350 | 0.5288 | |
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| 0.5414 | 1.8049 | 400 | 0.5243 | |
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| 0.5285 | 2.0305 | 450 | 0.5212 | |
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| 0.4729 | 2.2561 | 500 | 0.5180 | |
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| 0.5167 | 2.4817 | 550 | 0.5161 | |
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| 0.5228 | 2.7073 | 600 | 0.5141 | |
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| 0.5321 | 2.9329 | 650 | 0.5124 | |
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| 0.5212 | 3.1585 | 700 | 0.5112 | |
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| 0.5052 | 3.3841 | 750 | 0.5097 | |
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| 0.4826 | 3.6097 | 800 | 0.5088 | |
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| 0.5118 | 3.8353 | 850 | 0.5079 | |
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| 0.4957 | 4.0609 | 900 | 0.5071 | |
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| 0.4779 | 4.2865 | 950 | 0.5065 | |
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| 0.4888 | 4.5121 | 1000 | 0.5061 | |
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| 0.52 | 4.7377 | 1050 | 0.5055 | |
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| 0.4892 | 4.9633 | 1100 | 0.5052 | |
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| 0.4881 | 5.1889 | 1150 | 0.5051 | |
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| 0.5071 | 5.4146 | 1200 | 0.5047 | |
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| 0.515 | 5.6402 | 1250 | 0.5046 | |
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| 0.491 | 5.8658 | 1300 | 0.5045 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
