story_points_estimator
This model is a fine-tuned version of bert-large-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.5010
- Accuracy: 0.2581
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 35 | 1.5660 | 0.2903 |
No log | 2.0 | 70 | 1.5116 | 0.2903 |
No log | 3.0 | 105 | 1.5010 | 0.2581 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.0.0.post200
- Datasets 2.19.2
- Tokenizers 0.19.1
- Downloads last month
- 4
Model tree for lhn004/story_points_estimator
Base model
google-bert/bert-large-uncased