lotto
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3929
- Accuracy: 0.1383
- Precision: 0.1383
- Recall: 0.1383
- F1: 0.1383
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
0.4559 | 1.0 | 18 | 0.4474 | 0.1583 | 0.1583 | 0.1583 | 0.1583 |
0.4029 | 2.0 | 36 | 0.3972 | 0.1333 | 0.1333 | 0.1333 | 0.1333 |
0.3953 | 3.0 | 54 | 0.3924 | 0.135 | 0.135 | 0.135 | 0.135 |
0.3956 | 4.0 | 72 | 0.3926 | 0.1483 | 0.1483 | 0.1483 | 0.1483 |
0.3983 | 5.0 | 90 | 0.3933 | 0.1417 | 0.1417 | 0.1417 | 0.1417 |
0.3924 | 6.0 | 108 | 0.3926 | 0.1367 | 0.1367 | 0.1367 | 0.1367 |
0.3917 | 7.0 | 126 | 0.3926 | 0.1417 | 0.1417 | 0.1417 | 0.1417 |
0.3923 | 8.0 | 144 | 0.3924 | 0.1483 | 0.1483 | 0.1483 | 0.1483 |
0.3965 | 9.0 | 162 | 0.3929 | 0.1350 | 0.135 | 0.135 | 0.135 |
0.3939 | 10.0 | 180 | 0.3929 | 0.1383 | 0.1383 | 0.1383 | 0.1383 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.2.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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