| | --- |
| | base_model: microsoft/Phi-3.5-mini-instruct |
| | library_name: peft |
| | license: mit |
| | tags: |
| | - trl |
| | - sft |
| | - generated_from_trainer |
| | model-index: |
| | - name: Phi-3.5-MultiCap-mt |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # Phi-3.5-MultiCap-mt |
| |
|
| | 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. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.7569 |
| |
|
| | ## Model description |
| |
|
| | More information needed |
| |
|
| | ## Intended uses & limitations |
| |
|
| | More information needed |
| |
|
| | ## Training and evaluation data |
| |
|
| | More information needed |
| |
|
| | ## Training procedure |
| |
|
| | ### Training hyperparameters |
| |
|
| | The following hyperparameters were used during training: |
| | - learning_rate: 0.0001 |
| | - train_batch_size: 16 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 8 |
| | - total_train_batch_size: 128 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_ratio: 0.03 |
| | - num_epochs: 2 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:------:|:----:|:---------------:| |
| | | 1.4288 | 0.1533 | 15 | 1.3449 | |
| | | 1.0894 | 0.3065 | 30 | 1.1240 | |
| | | 0.9541 | 0.4598 | 45 | 0.9830 | |
| | | 0.9216 | 0.6130 | 60 | 0.8949 | |
| | | 0.8675 | 0.7663 | 75 | 0.8414 | |
| | | 0.8007 | 0.9195 | 90 | 0.8108 | |
| | | 0.8205 | 1.0728 | 105 | 0.7919 | |
| | | 0.7864 | 1.2261 | 120 | 0.7794 | |
| | | 0.7983 | 1.3793 | 135 | 0.7705 | |
| | | 0.7784 | 1.5326 | 150 | 0.7641 | |
| | | 0.744 | 1.6858 | 165 | 0.7595 | |
| | | 0.7765 | 1.8391 | 180 | 0.7569 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - PEFT 0.12.0 |
| | - Transformers 4.44.2 |
| | - Pytorch 2.4.0+cu124 |
| | - Datasets 2.21.0 |
| | - Tokenizers 0.19.1 |
