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:
- spearmanr
model-index:
- name: scenario-KD-SCR-DIV2-data-glue-stsb-model-bert-base-uncased-run-1
  results: []
---

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# scenario-KD-SCR-DIV2-data-glue-stsb-model-bert-base-uncased-run-1

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: 0.8481
- Pearson: 0.8723
- Spearmanr: 0.8710

## 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: 42
- 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 | Pearson | Spearmanr |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|
| No log        | 1.0   | 180  | 1.0815          | 0.8444  | 0.8397    |
| No log        | 2.0   | 360  | 0.9910          | 0.8542  | 0.8507    |
| 1.3016        | 3.0   | 540  | 0.9434          | 0.8552  | 0.8520    |
| 1.3016        | 4.0   | 720  | 0.9452          | 0.8615  | 0.8588    |
| 1.3016        | 5.0   | 900  | 0.8691          | 0.8659  | 0.8644    |
| 0.5631        | 6.0   | 1080 | 0.8851          | 0.8653  | 0.8635    |
| 0.5631        | 7.0   | 1260 | 0.8679          | 0.8644  | 0.8636    |
| 0.5631        | 8.0   | 1440 | 0.8904          | 0.8648  | 0.8632    |
| 0.4686        | 9.0   | 1620 | 0.8492          | 0.8671  | 0.8645    |
| 0.4686        | 10.0  | 1800 | 0.8952          | 0.8693  | 0.8682    |
| 0.4686        | 11.0  | 1980 | 0.8322          | 0.8712  | 0.8703    |
| 0.4268        | 12.0  | 2160 | 0.8227          | 0.8721  | 0.8692    |
| 0.4268        | 13.0  | 2340 | 0.7973          | 0.8746  | 0.8715    |
| 0.4018        | 14.0  | 2520 | 0.8366          | 0.8689  | 0.8678    |
| 0.4018        | 15.0  | 2700 | 0.7996          | 0.8724  | 0.8693    |
| 0.4018        | 16.0  | 2880 | 0.8277          | 0.8689  | 0.8678    |
| 0.3815        | 17.0  | 3060 | 0.8692          | 0.8656  | 0.8640    |
| 0.3815        | 18.0  | 3240 | 0.8481          | 0.8723  | 0.8710    |


### Framework versions

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