bert-base-uncased_relevance_extractor_secondary_binary
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2620
- F1: 0.8404
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: 6e-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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| No log | 1.0 | 24 | 0.2620 | 0.8404 |
| No log | 2.0 | 48 | 0.3159 | 0.8522 |
| No log | 3.0 | 72 | 0.2905 | 0.8604 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.13.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1
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Model tree for liy140/bert-base-uncased_relevance_extractor_secondary_binary
Base model
google-bert/bert-base-uncased