metadata
license: other
base_model: facebook/opt-350m
tags:
- trl
- reward-trainer
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: reward_modeling_anthropic_hh_rm1e-3
results: []
reward_modeling_anthropic_hh_rm1e-3
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: 0.6931
- Accuracy: 0.9951
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: 0.001
- 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 |
---|---|---|---|---|
0.6998 | 0.1087 | 500 | 0.6931 | 0.7465 |
0.7074 | 0.2174 | 1000 | 0.6931 | 0.6653 |
0.6924 | 0.3262 | 1500 | 0.6931 | 0.7551 |
0.6985 | 0.4349 | 2000 | 0.6931 | 0.6347 |
0.6939 | 0.5436 | 2500 | 0.6931 | 0.7825 |
0.6978 | 0.6523 | 3000 | 0.6931 | 0.9096 |
0.6974 | 0.7610 | 3500 | 0.6931 | 0.9584 |
0.6935 | 0.8698 | 4000 | 0.6931 | 0.9607 |
0.6962 | 0.9785 | 4500 | 0.6931 | 0.9951 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1