transformers pytorch 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-qnli-model-bert-base-uncased-run-3
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# scenario-KD-PRE-DIV2-data-glue-qnli-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: 1.8270
- Accuracy: 0.8596

## 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: 16
- eval_batch_size: 32
- seed: 45
- 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
- num_epochs: 6969

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.5227        | 1.0   | 3273  | 1.6868          | 0.8596   |
| 1.6366        | 2.0   | 6547  | 1.6143          | 0.8539   |
| 1.1125        | 3.0   | 9820  | 1.7793          | 0.8521   |
| 0.8908        | 4.0   | 13094 | 1.6376          | 0.8642   |
| 0.7217        | 5.0   | 16367 | 1.7602          | 0.8545   |
| 0.673         | 6.0   | 19641 | 1.6412          | 0.8634   |
| 0.5869        | 7.0   | 22914 | 1.6810          | 0.8611   |
| 0.5455        | 8.0   | 26188 | 1.5553          | 0.8662   |
| 0.506         | 9.0   | 29461 | 1.6137          | 0.8666   |
| 0.4771        | 10.0  | 32735 | 1.6643          | 0.8616   |
| 0.448         | 11.0  | 36008 | 1.5750          | 0.8666   |
| 0.4227        | 12.0  | 39282 | 1.5342          | 0.8678   |
| 0.4109        | 13.0  | 42555 | 1.6987          | 0.8638   |
| 0.3761        | 14.0  | 45829 | 1.6144          | 0.8645   |
| 0.3548        | 15.0  | 49102 | 1.6813          | 0.8605   |
| 0.3471        | 16.0  | 52376 | 1.6060          | 0.8656   |
| 0.3511        | 17.0  | 55649 | 1.8270          | 0.8596   |


### Framework versions

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