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-qqp-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-SCR-DIV2-data-glue-qqp-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: 1.1690
- Accuracy: 0.8946

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.9152        | 0.18  | 2000  | 2.4417          | 0.8369   |
| 2.4779        | 0.35  | 4000  | 1.9345          | 0.8583   |
| 2.2761        | 0.53  | 6000  | 1.8134          | 0.8619   |
| 2.1448        | 0.7   | 8000  | 1.5860          | 0.8708   |
| 2.0302        | 0.88  | 10000 | 1.5282          | 0.8777   |
| 1.4533        | 1.06  | 12000 | 1.6120          | 0.8772   |
| 1.4496        | 1.23  | 14000 | 1.5749          | 0.8808   |
| 1.4234        | 1.41  | 16000 | 1.4919          | 0.8825   |
| 1.4338        | 1.58  | 18000 | 1.4211          | 0.8822   |
| 1.4192        | 1.76  | 20000 | 1.4100          | 0.8847   |
| 1.3808        | 1.93  | 22000 | 1.3016          | 0.8855   |
| 0.986         | 2.11  | 24000 | 1.2934          | 0.8865   |
| 0.9904        | 2.29  | 26000 | 1.2920          | 0.8865   |
| 1.0213        | 2.46  | 28000 | 1.4134          | 0.8846   |
| 1.034         | 2.64  | 30000 | 1.2824          | 0.8891   |
| 1.0789        | 2.81  | 32000 | 1.3398          | 0.8886   |
| 1.0891        | 2.99  | 34000 | 1.4963          | 0.8886   |
| 0.7833        | 3.17  | 36000 | 1.2970          | 0.8893   |
| 0.8175        | 3.34  | 38000 | 1.3134          | 0.8918   |
| 0.8505        | 3.52  | 40000 | 1.3805          | 0.8885   |
| 0.8239        | 3.69  | 42000 | 1.2959          | 0.8921   |
| 0.8816        | 3.87  | 44000 | 1.3578          | 0.8919   |
| 0.6901        | 4.05  | 46000 | 1.3006          | 0.8908   |
| 0.6898        | 4.22  | 48000 | 1.2548          | 0.8905   |
| 0.7165        | 4.4   | 50000 | 1.3632          | 0.8926   |
| 0.72          | 4.57  | 52000 | 1.3347          | 0.8916   |
| 0.7202        | 4.75  | 54000 | 1.3214          | 0.8912   |
| 0.7318        | 4.93  | 56000 | 1.2439          | 0.8918   |
| 0.6155        | 5.1   | 58000 | 1.3010          | 0.8946   |
| 0.6067        | 5.28  | 60000 | 1.4221          | 0.8928   |
| 0.6321        | 5.45  | 62000 | 1.3804          | 0.8946   |
| 0.6426        | 5.63  | 64000 | 1.2464          | 0.8945   |
| 0.6543        | 5.8   | 66000 | 1.2338          | 0.8959   |
| 0.664         | 5.98  | 68000 | 1.2861          | 0.8951   |
| 0.5805        | 6.16  | 70000 | 1.2316          | 0.8954   |
| 0.57          | 6.33  | 72000 | 1.3224          | 0.8956   |
| 0.5802        | 6.51  | 74000 | 1.2094          | 0.8963   |
| 0.5797        | 6.68  | 76000 | 1.2334          | 0.8945   |
| 0.5974        | 6.86  | 78000 | 1.3467          | 0.8969   |
| 0.5422        | 7.04  | 80000 | 1.2513          | 0.8941   |
| 0.5227        | 7.21  | 82000 | 1.3624          | 0.8961   |
| 0.537         | 7.39  | 84000 | 1.2618          | 0.8973   |
| 0.5313        | 7.56  | 86000 | 1.2361          | 0.8957   |
| 0.5349        | 7.74  | 88000 | 1.1706          | 0.8971   |
| 0.5519        | 7.92  | 90000 | 1.2509          | 0.8950   |
| 0.4778        | 8.09  | 92000 | 1.2867          | 0.8966   |
| 0.4856        | 8.27  | 94000 | 1.1690          | 0.8946   |


### Framework versions

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