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SEED0042
This model is a fine-tuned version of bert-large-uncased on the MNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.5092
- Accuracy: 0.8573
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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: not_parallel
- gradient_accumulation_steps: 32
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4736 | 1.0 | 12271 | 0.4213 | 0.8372 |
| 0.3248 | 2.0 | 24542 | 0.4055 | 0.8538 |
| 0.1571 | 3.0 | 36813 | 0.5092 | 0.8573 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu113
- Datasets 2.1.0
- Tokenizers 0.11.6
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