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--- |
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base_model: microsoft/Phi-3.5-mini-instruct |
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datasets: |
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- generator |
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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-past |
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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-past |
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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 the generator dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7561 |
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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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| 1.1082 | 0.1524 | 50 | 1.1135 | |
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| 0.9647 | 0.3048 | 100 | 1.0051 | |
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| 0.9516 | 0.4571 | 150 | 0.9498 | |
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| 0.8882 | 0.6095 | 200 | 0.9027 | |
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| 0.9183 | 0.7619 | 250 | 0.8649 | |
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| 0.7923 | 0.9143 | 300 | 0.8355 | |
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| 0.8078 | 1.0667 | 350 | 0.8137 | |
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| 0.7677 | 1.2190 | 400 | 0.7969 | |
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| 0.765 | 1.3714 | 450 | 0.7822 | |
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| 0.812 | 1.5238 | 500 | 0.7720 | |
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| 0.7376 | 1.6762 | 550 | 0.7638 | |
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| 0.7617 | 1.8286 | 600 | 0.7586 | |
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| 0.7299 | 1.9810 | 650 | 0.7561 | |
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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 |
