metadata
library_name: transformers
base_model: Jennny/llama3_8b_sft_helpsteer
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: llama3_8b_helpsteer_coherence_rm
results: []
llama3_8b_helpsteer_coherence_rm
This model is a fine-tuned version of Jennny/llama3_8b_sft_helpsteer on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1530
- Accuracy: 0.5918
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.436 | 0.3042 | 10 | 0.9576 | 0.5765 |
| 0.14 | 0.6084 | 20 | 1.1787 | 0.6071 |
| 0.146 | 0.9125 | 30 | 0.8044 | 0.5561 |
| 0.0376 | 1.2433 | 40 | 1.5338 | 0.5714 |
| 0.0054 | 1.5475 | 50 | 1.1432 | 0.6020 |
| 0.0353 | 1.8517 | 60 | 1.0350 | 0.6173 |
| 0.0009 | 2.1825 | 70 | 1.1095 | 0.5867 |
| 0.0004 | 2.4867 | 80 | 1.1308 | 0.5867 |
| 0.0005 | 2.7909 | 90 | 1.1530 | 0.5918 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.1