Instructions to use Sushmita85/test_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Sushmita85/test_model with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/phi-1_5") model = PeftModel.from_pretrained(base_model, "Sushmita85/test_model") - Notebooks
- Google Colab
- Kaggle
| base_model: microsoft/phi-1_5 | |
| datasets: | |
| - samsum | |
| library_name: peft | |
| license: mit | |
| tags: | |
| - trl | |
| - sft | |
| - generated_from_trainer | |
| model-index: | |
| - name: test_model | |
| 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. --> | |
| # test_model | |
| This model is a fine-tuned version of [microsoft/phi-1_5](https://huggingface.co/microsoft/phi-1_5) on the samsum dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 3.0429 | |
| ## 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: 5e-07 | |
| - train_batch_size: 2 | |
| - eval_batch_size: 2 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 3 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | | |
| |:-------------:|:-----:|:----:|:---------------:| | |
| | 2.8377 | 1.0 | 250 | 3.0473 | | |
| | 2.9821 | 2.0 | 500 | 3.0425 | | |
| | 2.9724 | 3.0 | 750 | 3.0429 | | |
| ### Framework versions | |
| - PEFT 0.11.1 | |
| - Transformers 4.41.2 | |
| - Pytorch 2.3.0+cu121 | |
| - Datasets 2.20.0 | |
| - Tokenizers 0.19.1 |