6b-jilp
This model is a fine-tuned version of PygmalionAI/pygmalion-6b on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.9014
- Accuracy: 0.1213
- Entropy: 1.8265
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: 12
- eval_batch_size: 8
- seed: 99
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 5.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Entropy |
---|---|---|---|---|---|
2.5421 | 1.0 | 2815 | 1.9824 | 0.1183 | 2.0945 |
2.426 | 2.0 | 5630 | 1.9443 | 0.1197 | 1.9446 |
2.4504 | 3.0 | 8445 | 1.9248 | 0.1204 | 1.9272 |
2.4573 | 4.0 | 11260 | 1.9102 | 0.1211 | 1.8612 |
2.4421 | 5.0 | 14075 | 1.9014 | 0.1213 | 1.8265 |
Framework versions
- Transformers 4.28.1
- Pytorch 1.13.1
- Datasets 2.7.1
- Tokenizers 0.13.3