| | --- |
| | license: other |
| | library_name: peft |
| | tags: |
| | - llama-factory |
| | - lora |
| | - generated_from_trainer |
| | base_model: saves/Orca/merge_unload |
| | model-index: |
| | - name: SFT |
| | 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. --> |
| |
|
| | # SFT |
| |
|
| | This model is a fine-tuned version of [saves/Orca/merge_unload](https://huggingface.co/saves/Orca/merge_unload) on the WordProblems_SFT dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.1966 |
| | |
| | ## 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-05 |
| | - train_batch_size: 4 |
| | - eval_batch_size: 4 |
| | - seed: 42 |
| | - distributed_type: multi-GPU |
| | - num_devices: 4 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 32 |
| | - total_eval_batch_size: 16 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: cosine |
| | - lr_scheduler_warmup_steps: 300 |
| | - num_epochs: 2.0 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:------:|:----:|:---------------:| |
| | | 0.2823 | 0.2425 | 250 | 0.2783 | |
| | | 0.2186 | 0.4850 | 500 | 0.2229 | |
| | | 0.2227 | 0.7274 | 750 | 0.2104 | |
| | | 0.1965 | 0.9699 | 1000 | 0.2038 | |
| | | 0.2001 | 1.2124 | 1250 | 0.2003 | |
| | | 0.2087 | 1.4549 | 1500 | 0.1980 | |
| | | 0.1932 | 1.6974 | 1750 | 0.1969 | |
| | | 0.2044 | 1.9399 | 2000 | 0.1966 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - PEFT 0.10.0 |
| | - Transformers 4.40.2 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.17.1 |
| | - Tokenizers 0.19.1 |
