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-PRE-DIV2-data-glue-sst2-model-bert-base-uncased-run-3
  results: []
---

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# scenario-KD-PRE-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: 1.6751
- Accuracy: 0.8888

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.351         | 1.0   | 2105  | 2.2176          | 0.8658   |
| 0.7949        | 2.0   | 4210  | 1.9382          | 0.8876   |
| 0.5985        | 3.0   | 6315  | 1.7303          | 0.8922   |
| 0.4913        | 4.0   | 8420  | 1.7865          | 0.8876   |
| 0.3806        | 5.0   | 10525 | 1.9364          | 0.8739   |
| 0.3569        | 6.0   | 12630 | 1.7091          | 0.8865   |
| 0.3309        | 7.0   | 14735 | 1.5981          | 0.8853   |
| 0.3148        | 8.0   | 16840 | 1.6751          | 0.8888   |


### Framework versions

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