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---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
- Multiple Choice
metrics:
- accuracy
model-index:
- name: bert-base-uncased-e_CARE
results: []
datasets:
- 12ml/e-CARE
language:
- en
pipeline_tag: question-answering
---
# bert-base-uncased-e_CARE
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased).
It achieves the following results on the evaluation set:
- Loss: 1.7677
- Accuracy: 0.7212
## 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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5637 | 1.0 | 1571 | 0.5282 | 0.7244 |
| 0.345 | 2.0 | 3142 | 0.6667 | 0.7320 |
| 0.1098 | 3.0 | 4713 | 1.3113 | 0.7257 |
| 0.0212 | 4.0 | 6284 | 1.8194 | 0.7225 |
| 0.0185 | 5.0 | 7855 | 1.7677 | 0.7212 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.2
- Tokenizers 0.13.3 |