KUCI_albert_base_Finetuned
This model is a fine-tuned version of albert/albert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3234
- F1: 0.3702
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: 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: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 1.3324 | 1.0 | 5196 | 1.3209 | 0.3606 |
| 1.3295 | 2.0 | 10392 | 1.3197 | 0.3729 |
| 1.324 | 3.0 | 15588 | 1.3194 | 0.3644 |
| 1.3244 | 4.0 | 20784 | 1.3218 | 0.3604 |
| 1.3201 | 5.0 | 25980 | 1.3195 | 0.3647 |
| 1.3135 | 6.0 | 31176 | 1.3210 | 0.3646 |
| 1.3124 | 7.0 | 36372 | 1.3234 | 0.3702 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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