RM-HH-Mix_harmless_gpt3_20000_gemma2b_shuffleFalse_extractchosenFalse
This model is a fine-tuned version of google/gemma-2b on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0445
- Accuracy: 0.9815
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: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- 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 |
---|---|---|---|---|
0.8191 | 0.06 | 250 | 0.5824 | 0.695 |
0.6294 | 0.11 | 500 | 0.1346 | 0.953 |
0.5811 | 0.17 | 750 | 0.0888 | 0.9705 |
0.5753 | 0.22 | 1000 | 0.0684 | 0.975 |
0.5539 | 0.28 | 1250 | 0.0588 | 0.979 |
0.5764 | 0.33 | 1500 | 0.0595 | 0.9785 |
0.5261 | 0.39 | 1750 | 0.0558 | 0.979 |
0.5423 | 0.44 | 2000 | 0.0533 | 0.9795 |
0.5261 | 0.5 | 2250 | 0.0501 | 0.98 |
0.5363 | 0.56 | 2500 | 0.0485 | 0.98 |
0.5051 | 0.61 | 2750 | 0.0472 | 0.981 |
0.5157 | 0.67 | 3000 | 0.0509 | 0.9795 |
0.5368 | 0.72 | 3250 | 0.0507 | 0.9785 |
0.5281 | 0.78 | 3500 | 0.0467 | 0.981 |
0.5005 | 0.83 | 3750 | 0.0450 | 0.9815 |
0.5239 | 0.89 | 4000 | 0.0445 | 0.9815 |
0.5111 | 0.94 | 4250 | 0.0445 | 0.9815 |
Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for Holarissun/RM-HH-Mix_harmless_gpt3_20000_gemma2b_shuffleFalse_extractchosenFalse
Base model
google/gemma-2b