metadata
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-large-uncased_finetuning_distillation
results: []
bert-large-uncased_finetuning_distillation
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4721
- Accuracy: 0.8352
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.7395 | 1.39 | 500 | 0.8593 | 0.6847 |
| 0.6019 | 2.78 | 1000 | 0.5655 | 0.7949 |
| 0.3085 | 4.17 | 1500 | 0.4899 | 0.8293 |
| 0.1631 | 5.56 | 2000 | 0.4558 | 0.8475 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1