bert_large_uncased-QA1
This model is a fine-tuned version of google-bert/bert-large-uncased-whole-word-masking-finetuned-squad on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6158
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
- lr_scheduler_warmup_steps: 100
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 9 | 3.4299 |
| No log | 2.0 | 18 | 2.3637 |
| No log | 3.0 | 27 | 1.3157 |
| No log | 4.0 | 36 | 0.8384 |
| No log | 5.0 | 45 | 0.6158 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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