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
  results: []
---

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

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: 0.9266
- Pearson: 0.8665
- Spearmanr: 0.8640

## 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  | 1.3397          | 0.8445  | 0.8414    |
| No log        | 2.0   | 360  | 1.2294          | 0.8492  | 0.8460    |
| 1.4905        | 3.0   | 540  | 1.0923          | 0.8488  | 0.8464    |
| 1.4905        | 4.0   | 720  | 1.0628          | 0.8596  | 0.8559    |
| 1.4905        | 5.0   | 900  | 0.9989          | 0.8614  | 0.8585    |
| 0.6396        | 6.0   | 1080 | 0.9350          | 0.8672  | 0.8649    |
| 0.6396        | 7.0   | 1260 | 0.9412          | 0.8657  | 0.8640    |
| 0.6396        | 8.0   | 1440 | 0.9681          | 0.8629  | 0.8599    |
| 0.5193        | 9.0   | 1620 | 1.0704          | 0.8577  | 0.8560    |
| 0.5193        | 10.0  | 1800 | 1.0005          | 0.8622  | 0.8601    |
| 0.5193        | 11.0  | 1980 | 0.9266          | 0.8665  | 0.8640    |


### Framework versions

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