| | --- |
| | license: apache-2.0 |
| | library_name: peft |
| | tags: |
| | - trl |
| | - sft |
| | - generated_from_trainer |
| | datasets: |
| | - generator |
| | base_model: princeton-nlp/Sheared-LLaMA-1.3B |
| | model-index: |
| | - name: fluent-capybara-27-replication |
| | 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. --> |
| |
|
| | # fluent-capybara-27-replication |
| |
|
| | This model is a fine-tuned version of [princeton-nlp/Sheared-LLaMA-1.3B](https://huggingface.co/princeton-nlp/Sheared-LLaMA-1.3B) on the generator dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 2.2483 |
| |
|
| | ## 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: 2.5e-05 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 8 |
| | - seed: 100 |
| | - distributed_type: multi-GPU |
| | - num_devices: 4 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 128 |
| | - total_eval_batch_size: 32 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: cosine |
| | - lr_scheduler_warmup_steps: 200 |
| | - num_epochs: 5.0 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:-----:|:----:|:---------------:| |
| | | 2.7039 | 1.0 | 750 | 2.6816 | |
| | | 2.4411 | 2.0 | 1500 | 2.4269 | |
| | | 2.3104 | 3.0 | 2250 | 2.3173 | |
| | | 2.2149 | 4.0 | 3001 | 2.2593 | |
| | | 2.0649 | 5.0 | 3750 | 2.2483 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - PEFT 0.10.0 |
| | - Transformers 4.39.1 |
| | - Pytorch 2.1.2+cu118 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.15.1 |
