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1.3b-synthetic-v1-after-book
This model is a fine-tuned version of /models/1.3b-dalio-principles-book on the AlekseyKorshuk/dalio-synthetic-io dataset. It achieves the following results on the evaluation set:
- Loss: 1.9805
- Accuracy: 0.0754
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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- 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: cosine
- num_epochs: 1.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.0841 | 0.1 | 1 | 2.0254 | 0.0759 |
| 2.062 | 0.2 | 2 | 2.0254 | 0.0759 |
| 2.1509 | 0.3 | 3 | 1.9941 | 0.0761 |
| 2.1206 | 0.4 | 4 | 1.9941 | 0.0756 |
| 2.2087 | 0.5 | 5 | 1.9941 | 0.0757 |
| 2.0337 | 0.6 | 6 | 1.9902 | 0.0755 |
| 2.026 | 0.7 | 7 | 1.9854 | 0.0755 |
| 2.1879 | 0.8 | 8 | 1.9834 | 0.0756 |
| 2.1052 | 0.9 | 9 | 1.9824 | 0.0754 |
| 2.046 | 1.0 | 10 | 1.9805 | 0.0754 |
Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
