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
- f1
model-index:
- name: scenario-KD-SCR-DIV2-data-glue-mrpc-model-bert-base-uncased-run-3
  results: []
---

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# scenario-KD-SCR-DIV2-data-glue-mrpc-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: 8.1233
- Accuracy: 0.7623
- F1: 0.8412

## 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: 45
- 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 | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 115  | 8.3016          | 0.7034   | 0.8186 |
| No log        | 2.0   | 230  | 6.9667          | 0.7549   | 0.8387 |
| No log        | 3.0   | 345  | 8.0665          | 0.7328   | 0.8050 |
| No log        | 4.0   | 460  | 9.3725          | 0.7255   | 0.7993 |
| 6.6411        | 5.0   | 575  | 10.9233         | 0.7377   | 0.8386 |
| 6.6411        | 6.0   | 690  | 9.3717          | 0.7745   | 0.8535 |
| 6.6411        | 7.0   | 805  | 9.4175          | 0.7598   | 0.8409 |
| 6.6411        | 8.0   | 920  | 8.7530          | 0.7574   | 0.8331 |
| 1.26          | 9.0   | 1035 | 8.0672          | 0.7966   | 0.8637 |
| 1.26          | 10.0  | 1150 | 9.4575          | 0.7672   | 0.8330 |
| 1.26          | 11.0  | 1265 | 9.4591          | 0.7623   | 0.8246 |
| 1.26          | 12.0  | 1380 | 9.4565          | 0.7721   | 0.8426 |
| 1.26          | 13.0  | 1495 | 9.0076          | 0.7647   | 0.8367 |
| 0.8397        | 14.0  | 1610 | 8.1233          | 0.7623   | 0.8412 |


### Framework versions

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