Instructions to use ajrayman/personality_final_seed1234_fold1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ajrayman/personality_final_seed1234_fold1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ajrayman/personality_final_seed1234_fold1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
personality_final_seed1234_fold1
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8611
- Mean Rmse: 0.9269
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 1235
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 12
Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Rmse |
|---|---|---|---|---|
| No log | 1.0 | 339 | 0.8623 | 0.9292 |
| 0.9156 | 2.0 | 678 | 0.8335 | 0.9132 |
| 0.8177 | 3.0 | 1017 | 0.8363 | 0.9139 |
| 0.8177 | 4.0 | 1356 | 0.8485 | 0.9185 |
| 0.7252 | 5.0 | 1695 | 0.8611 | 0.9269 |
Framework versions
- Transformers 4.44.1
- Pytorch 1.11.0
- Datasets 2.12.0
- Tokenizers 0.19.1
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