| tags: | |
| - generated_from_trainer | |
| model-index: | |
| - name: starcoder-ift | |
| 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. --> | |
| # starcoder-ift | |
| This model is a fine-tuned version of [bigcode/large-model](https://huggingface.co/bigcode/large-model) on the None dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 1.4943 | |
| ## 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: 2e-05 | |
| - train_batch_size: 2 | |
| - eval_batch_size: 2 | |
| - seed: 42 | |
| - distributed_type: multi-GPU | |
| - num_devices: 8 | |
| - gradient_accumulation_steps: 8 | |
| - total_train_batch_size: 128 | |
| - total_eval_batch_size: 16 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: cosine | |
| - lr_scheduler_warmup_ratio: 0.03 | |
| - num_epochs: 3 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | | |
| |:-------------:|:-----:|:----:|:---------------:| | |
| | 1.6668 | 0.99 | 65 | 1.6167 | | |
| | 1.3584 | 2.0 | 131 | 1.5126 | | |
| | 1.0949 | 2.98 | 195 | 1.4943 | | |
| ### Framework versions | |
| - Transformers 4.28.1 | |
| - Pytorch 1.13.1+cu117 | |
| - Datasets 2.12.0 | |
| - Tokenizers 0.13.3 | |