COPA_Bert_Base_Uncased_Finetuned
This model is a fine-tuned version of google-bert/bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5670
- F1: 0.7384
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: 10
Training results
Training Loss | Epoch | Step | Validation Loss | F1 |
---|---|---|---|---|
No log | 1.0 | 63 | 0.6878 | 0.5954 |
No log | 2.0 | 126 | 0.6608 | 0.6680 |
No log | 3.0 | 189 | 0.6181 | 0.6887 |
No log | 4.0 | 252 | 0.5839 | 0.7219 |
No log | 5.0 | 315 | 0.5627 | 0.7219 |
No log | 6.0 | 378 | 0.5537 | 0.7280 |
No log | 7.0 | 441 | 0.5613 | 0.7319 |
0.5359 | 8.0 | 504 | 0.5636 | 0.7335 |
0.5359 | 9.0 | 567 | 0.5676 | 0.7326 |
0.5359 | 10.0 | 630 | 0.5670 | 0.7384 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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