albert_v2_lookup_spending_category
This model is a fine-tuned version of Palak/albert-base-v2_squad on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0406
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 84 | 0.0321 |
| No log | 2.0 | 168 | 0.0358 |
| No log | 3.0 | 252 | 0.0372 |
| No log | 4.0 | 336 | 0.0381 |
| No log | 5.0 | 420 | 0.0388 |
| 0.0064 | 6.0 | 504 | 0.0393 |
| 0.0064 | 7.0 | 588 | 0.0398 |
| 0.0064 | 8.0 | 672 | 0.0401 |
| 0.0064 | 9.0 | 756 | 0.0403 |
| 0.0064 | 10.0 | 840 | 0.0405 |
| 0.0064 | 11.0 | 924 | 0.0406 |
| 0.0 | 12.0 | 1008 | 0.0406 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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Model tree for kranasian/albert_v2_lookup_spending_category
Base model
Palak/albert-base-v2_squad