transformers safetensors bert generated_from_trainer base_model:bert-base-uncased license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: scenario-KD-SCR-DIV2-data-glue-sst2-model-bert-base-uncased-run-3
  results: []
---

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# scenario-KD-SCR-DIV2-data-glue-sst2-model-bert-base-uncased-run-3

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8394
- Accuracy: 0.8911

## 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: 32
- eval_batch_size: 32
- seed: 45
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6969

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.379         | 1.0   | 2105  | 1.9908          | 0.8784   |
| 0.8041        | 2.0   | 4210  | 1.6913          | 0.8865   |
| 0.6181        | 3.0   | 6315  | 1.9046          | 0.8784   |
| 0.4617        | 4.0   | 8420  | 1.6333          | 0.8922   |
| 0.41          | 5.0   | 10525 | 1.8034          | 0.8830   |
| 0.351         | 6.0   | 12630 | 1.8450          | 0.8899   |
| 0.32          | 7.0   | 14735 | 1.9411          | 0.8842   |
| 0.2927        | 8.0   | 16840 | 1.7726          | 0.8991   |
| 0.2771        | 9.0   | 18945 | 1.6832          | 0.8807   |
| 0.2565        | 10.0  | 21050 | 1.6899          | 0.8933   |
| 0.2434        | 11.0  | 23155 | 1.7471          | 0.8888   |
| 0.23          | 12.0  | 25260 | 2.1582          | 0.8704   |
| 0.2255        | 13.0  | 27365 | 1.8486          | 0.9037   |
| 0.2041        | 14.0  | 29470 | 1.6787          | 0.8922   |
| 0.218         | 15.0  | 31575 | 1.8426          | 0.8888   |
| 0.2027        | 16.0  | 33680 | 1.8820          | 0.8945   |
| 0.1924        | 17.0  | 35785 | 1.9447          | 0.8933   |
| 0.1964        | 18.0  | 37890 | 1.8394          | 0.8911   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.16.0
- Tokenizers 0.15.0
