| --- |
| library_name: transformers |
| base_model: Jennny/llama3_8b_sft_helpsteer |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: llama3_8b_helpsteer_correct_rm |
| 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. --> |
|
|
| # llama3_8b_helpsteer_correct_rm |
|
|
| This model is a fine-tuned version of [Jennny/llama3_8b_sft_helpsteer](https://huggingface.co/Jennny/llama3_8b_sft_helpsteer) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.5813 |
| - Accuracy: 0.5847 |
|
|
| ## 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: 1e-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: Use OptimizerNames.PAGED_ADAMW with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_ratio: 0.03 |
| - num_epochs: 2 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | 0.1608 | 0.1882 | 10 | 1.1481 | 0.5847 | |
| | 0.128 | 0.3765 | 20 | 0.8165 | 0.6045 | |
| | 0.1509 | 0.5647 | 30 | 0.7681 | 0.6271 | |
| | 0.1323 | 0.7529 | 40 | 0.8492 | 0.5650 | |
| | 0.0856 | 0.9412 | 50 | 0.9250 | 0.6073 | |
| | 0.0013 | 1.1129 | 60 | 1.2136 | 0.6073 | |
| | 0.0088 | 1.3012 | 70 | 1.7243 | 0.5593 | |
| | 0.034 | 1.4894 | 80 | 1.7962 | 0.5650 | |
| | 0.0083 | 1.6776 | 90 | 1.6045 | 0.5763 | |
| | 0.0001 | 1.8659 | 100 | 1.5813 | 0.5847 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.49.0 |
| - Pytorch 2.5.1+cu124 |
| - Datasets 3.3.2 |
| - Tokenizers 0.21.1 |
| |
