fundhub_fund_v1
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: 5.6734
- F1: 0.0078
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: 16
- 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 | F1 |
|---|---|---|---|---|
| 5.4004 | 1.0 | 23928 | 5.5930 | 0.0078 |
| 5.3216 | 2.0 | 47856 | 5.6629 | 0.0078 |
| 5.1948 | 3.0 | 71784 | 5.6734 | 0.0078 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.4
- Tokenizers 0.14.1
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Model tree for raminm/fundhub_fund_v1
Base model
google-bert/bert-large-uncased