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-PRE-DIV2-data-glue-stsb-model-bert-base-uncased-run-1
  results: []
---

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# scenario-KD-PRE-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: 0.8263
- Pearson: 0.8675
- Spearmanr: 0.8653

## 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  | 1.2416          | 0.8419  | 0.8380    |
| No log        | 2.0   | 360  | 1.0332          | 0.8520  | 0.8486    |
| 1.344         | 3.0   | 540  | 0.9422          | 0.8570  | 0.8535    |
| 1.344         | 4.0   | 720  | 0.9650          | 0.8586  | 0.8544    |
| 1.344         | 5.0   | 900  | 0.8822          | 0.8656  | 0.8640    |
| 0.5696        | 6.0   | 1080 | 0.8523          | 0.8668  | 0.8638    |
| 0.5696        | 7.0   | 1260 | 0.8368          | 0.8680  | 0.8654    |
| 0.5696        | 8.0   | 1440 | 0.8537          | 0.8657  | 0.8638    |
| 0.4656        | 9.0   | 1620 | 0.8939          | 0.8654  | 0.8632    |
| 0.4656        | 10.0  | 1800 | 0.9344          | 0.8672  | 0.8661    |
| 0.4656        | 11.0  | 1980 | 0.8518          | 0.8666  | 0.8650    |
| 0.4253        | 12.0  | 2160 | 0.7979          | 0.8734  | 0.8705    |
| 0.4253        | 13.0  | 2340 | 0.8395          | 0.8666  | 0.8656    |
| 0.3975        | 14.0  | 2520 | 0.8213          | 0.8694  | 0.8675    |
| 0.3975        | 15.0  | 2700 | 0.8461          | 0.8676  | 0.8655    |
| 0.3975        | 16.0  | 2880 | 0.8548          | 0.8668  | 0.8649    |
| 0.3772        | 17.0  | 3060 | 0.8263          | 0.8675  | 0.8653    |


### Framework versions

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