metadata
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: gptneo-1.3B-rm-harmless
results: []
gptneo-1.3B-rm-harmless
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5449
- Accuracy: 0.7184
- Average Pos Score: 1.1621
- Average Neg Score: 0.4114
- Average Abs Score Diff: 1.1133
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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Average Pos Score | Average Neg Score | Average Abs Score Diff |
|---|---|---|---|---|---|---|---|
| 0.6274 | 0.15 | 200 | 0.5898 | 0.6968 | 1.7881 | 1.2979 | 0.8413 |
| 0.5058 | 0.3 | 400 | 0.5811 | 0.7115 | 0.8394 | -0.0314 | 1.3799 |
| 0.5699 | 0.45 | 600 | 0.5527 | 0.7167 | 1.2803 | 0.6006 | 1.0293 |
| 0.5533 | 0.6 | 800 | 0.5542 | 0.7171 | 0.6689 | -0.1876 | 1.2930 |
| 0.5396 | 0.75 | 1000 | 0.5444 | 0.7223 | 1.0977 | 0.3601 | 1.0977 |
| 0.5791 | 0.9 | 1200 | 0.5449 | 0.7184 | 1.1621 | 0.4114 | 1.1133 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.12.1+cu113
- Datasets 2.9.0
- Tokenizers 0.13.2