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-1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# scenario-KD-SCR-DIV2-data-glue-mrpc-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: 9.9589
- Accuracy: 0.7549
- F1: 0.8282

## 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 | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 115  | 8.5498          | 0.7108   | 0.8066 |
| No log        | 2.0   | 230  | 7.3326          | 0.7402   | 0.8354 |
| No log        | 3.0   | 345  | 7.5550          | 0.7721   | 0.8488 |
| No log        | 4.0   | 460  | 8.2672          | 0.75     | 0.8217 |
| 6.456         | 5.0   | 575  | 9.2231          | 0.7451   | 0.8219 |
| 6.456         | 6.0   | 690  | 9.8559          | 0.7353   | 0.8138 |
| 6.456         | 7.0   | 805  | 9.6011          | 0.7623   | 0.8412 |
| 6.456         | 8.0   | 920  | 8.6035          | 0.7770   | 0.8539 |
| 1.0616        | 9.0   | 1035 | 9.1009          | 0.7672   | 0.8398 |
| 1.0616        | 10.0  | 1150 | 9.4293          | 0.7672   | 0.8348 |
| 1.0616        | 11.0  | 1265 | 10.9628         | 0.7402   | 0.8051 |
| 1.0616        | 12.0  | 1380 | 10.5976         | 0.7598   | 0.8212 |
| 1.0616        | 13.0  | 1495 | 9.9589          | 0.7549   | 0.8282 |


### Framework versions

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