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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-tool-embedding |
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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-tool-embedding |
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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: 0.5080 |
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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: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.6813 | 0.2256 | 50 | 0.6682 | |
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| 0.5534 | 0.4512 | 100 | 0.5627 | |
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| 0.5291 | 0.6768 | 150 | 0.5372 | |
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| 0.575 | 0.9024 | 200 | 0.5245 | |
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| 0.5066 | 1.1280 | 250 | 0.5170 | |
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| 0.4949 | 1.3536 | 300 | 0.5124 | |
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| 0.4666 | 1.5792 | 350 | 0.5095 | |
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| 0.5142 | 1.8049 | 400 | 0.5080 | |
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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 3.0.0 |
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- Tokenizers 0.19.1 |
