orderlyai
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 5.8317
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 46 | 2.5961 |
| No log | 2.0 | 92 | 2.9959 |
| No log | 3.0 | 138 | 3.6266 |
| No log | 4.0 | 184 | 4.3102 |
| No log | 5.0 | 230 | 4.7747 |
| No log | 6.0 | 276 | 5.1535 |
| No log | 7.0 | 322 | 5.4790 |
| No log | 8.0 | 368 | 5.6904 |
| No log | 9.0 | 414 | 5.7965 |
| No log | 10.0 | 460 | 5.8317 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for withorderlyai/orderlyai
Base model
google-bert/bert-base-uncased