reward_modeling_anthropic_hh_rm0.99
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: 0.5922
- Accuracy: 0.6716
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: 1.41e-05
- 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 |
---|---|---|---|---|
0.6448 | 0.1087 | 500 | 0.6522 | 0.6180 |
0.6105 | 0.2174 | 1000 | 0.6485 | 0.6234 |
0.6453 | 0.3262 | 1500 | 0.6207 | 0.6409 |
0.6357 | 0.4349 | 2000 | 0.6204 | 0.6543 |
0.6149 | 0.5436 | 2500 | 0.6132 | 0.6557 |
0.6198 | 0.6523 | 3000 | 0.6047 | 0.6644 |
0.6076 | 0.7610 | 3500 | 0.5999 | 0.6618 |
0.6182 | 0.8698 | 4000 | 0.5948 | 0.6711 |
0.588 | 0.9785 | 4500 | 0.5922 | 0.6716 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for alexwb/reward_modeling_anthropic_hh_rm0.99
Base model
facebook/opt-350m