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:
- matthews_correlation
model-index:
- name: scenario-KD-PRE-DIV2-data-glue-cola-model-bert-base-uncased-run-2
  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-cola-model-bert-base-uncased-run-2

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: 1.5125
- Matthews Correlation: 0.4073

## 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: 43
- 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 | Matthews Correlation |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|
| No log        | 1.0   | 268  | 1.6077          | 0.3327               |
| 1.9068        | 2.0   | 536  | 1.5135          | 0.3528               |
| 1.9068        | 3.0   | 804  | 1.5900          | 0.3592               |
| 0.8121        | 4.0   | 1072 | 1.6949          | 0.3861               |
| 0.8121        | 5.0   | 1340 | 1.6394          | 0.3982               |
| 0.591         | 6.0   | 1608 | 1.8460          | 0.3287               |
| 0.591         | 7.0   | 1876 | 1.4780          | 0.4116               |
| 0.4848        | 8.0   | 2144 | 1.5955          | 0.4099               |
| 0.4848        | 9.0   | 2412 | 1.5258          | 0.4285               |
| 0.4247        | 10.0  | 2680 | 1.4068          | 0.4379               |
| 0.4247        | 11.0  | 2948 | 1.5005          | 0.4082               |
| 0.3814        | 12.0  | 3216 | 1.4648          | 0.4397               |
| 0.3814        | 13.0  | 3484 | 1.5061          | 0.4046               |
| 0.3535        | 14.0  | 3752 | 1.4025          | 0.4106               |
| 0.3228        | 15.0  | 4020 | 1.4939          | 0.4327               |
| 0.3228        | 16.0  | 4288 | 1.4414          | 0.4477               |
| 0.3104        | 17.0  | 4556 | 1.4777          | 0.4636               |
| 0.3104        | 18.0  | 4824 | 1.4170          | 0.4384               |
| 0.293         | 19.0  | 5092 | 1.4852          | 0.4159               |
| 0.293         | 20.0  | 5360 | 1.4573          | 0.4141               |
| 0.2761        | 21.0  | 5628 | 1.5367          | 0.4428               |
| 0.2761        | 22.0  | 5896 | 1.5125          | 0.4073               |


### Framework versions

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