reward_modeling_anthropic_hh_rm1e-6
This model is a fine-tuned version of facebook/opt-350m on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6426
- Accuracy: 0.6277
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-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.6812 | 0.1087 | 500 | 0.6965 | 0.5592 |
0.6554 | 0.2174 | 1000 | 0.6798 | 0.5765 |
0.6715 | 0.3262 | 1500 | 0.6699 | 0.5850 |
0.6401 | 0.4349 | 2000 | 0.6635 | 0.5932 |
0.6741 | 0.5436 | 2500 | 0.6555 | 0.6093 |
0.653 | 0.6523 | 3000 | 0.6504 | 0.6185 |
0.6446 | 0.7610 | 3500 | 0.6456 | 0.6227 |
0.6449 | 0.8698 | 4000 | 0.6434 | 0.6250 |
0.6597 | 0.9785 | 4500 | 0.6426 | 0.6277 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Downloads last month
- 0
Model tree for alexwb/reward_modeling_anthropic_hh_rm1e-6
Base model
facebook/opt-350m
Finetuned
this model