| | --- |
| | 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 |
| | 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 |
| |
|
| | 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: 0.5367 |
| |
|
| | ## 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 | |
| | |:-------------:|:------:|:----:|:---------------:| |
| | | 1.0783 | 0.1354 | 30 | 1.0955 | |
| | | 0.716 | 0.2707 | 60 | 0.7190 | |
| | | 0.6167 | 0.4061 | 90 | 0.6266 | |
| | | 0.6226 | 0.5415 | 120 | 0.5929 | |
| | | 0.5665 | 0.6768 | 150 | 0.5737 | |
| | | 0.5834 | 0.8122 | 180 | 0.5621 | |
| | | 0.5931 | 0.9475 | 210 | 0.5549 | |
| | | 0.5431 | 1.0829 | 240 | 0.5496 | |
| | | 0.5678 | 1.2183 | 270 | 0.5458 | |
| | | 0.5336 | 1.3536 | 300 | 0.5425 | |
| | | 0.5292 | 1.4890 | 330 | 0.5403 | |
| | | 0.5627 | 1.6244 | 360 | 0.5384 | |
| | | 0.5493 | 1.7597 | 390 | 0.5374 | |
| | | 0.5154 | 1.8951 | 420 | 0.5367 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - PEFT 0.12.0 |
| | - Transformers 4.44.2 |
| | - Pytorch 2.4.0+cu124 |
| | - Datasets 2.21.0 |
| | - Tokenizers 0.19.1 |
