<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
1.3b-dalio-principles-book
This model is a fine-tuned version of facebook/opt-1.3b on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.4512
- Accuracy: 0.4741
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: 7e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 8
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.6914 | 0.14 | 1 | 2.6895 | 0.4477 |
| 2.6897 | 0.29 | 2 | 2.6895 | 0.4477 |
| 2.668 | 0.43 | 3 | 2.7031 | 0.4403 |
| 2.7434 | 0.57 | 4 | 2.5918 | 0.4533 |
| 2.6265 | 0.71 | 5 | 2.5410 | 0.4618 |
| 2.5259 | 0.86 | 6 | 2.5156 | 0.4641 |
| 2.5566 | 1.0 | 7 | 2.4902 | 0.4667 |
| 2.2317 | 1.14 | 8 | 2.4766 | 0.4707 |
| 2.2397 | 1.29 | 9 | 2.4727 | 0.4705 |
| 2.0162 | 1.43 | 10 | 2.4766 | 0.4690 |
| 2.0537 | 1.57 | 11 | 2.4805 | 0.4707 |
| 2.1432 | 1.71 | 12 | 2.4707 | 0.4714 |
| 2.0822 | 1.86 | 13 | 2.4570 | 0.4724 |
| 1.9056 | 2.0 | 14 | 2.4512 | 0.4741 |
Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
