metadata
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-cased
tags:
- text-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: trainer
results: []
trainer
This model is a fine-tuned version of google-bert/bert-base-cased on the TalonMeyer/URAP_interview_task_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.0491
- Accuracy: 0.9910
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0675 | 1.0 | 1000 | 0.0594 | 0.9895 |
| 0.0351 | 2.0 | 2000 | 0.0408 | 0.9925 |
| 0.0227 | 3.0 | 3000 | 0.0491 | 0.9910 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1