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-PRE-DIV2-data-glue-mrpc-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-mrpc-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: 8.6408
- Accuracy: 0.7623
- F1: 0.8336

## 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 | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 115  | 7.6531          | 0.7181   | 0.8286 |
| No log        | 2.0   | 230  | 6.9372          | 0.7451   | 0.8169 |
| No log        | 3.0   | 345  | 7.9178          | 0.7451   | 0.8188 |
| No log        | 4.0   | 460  | 7.5428          | 0.7549   | 0.8311 |
| 5.7149        | 5.0   | 575  | 8.4417          | 0.7402   | 0.8160 |
| 5.7149        | 6.0   | 690  | 8.5841          | 0.7598   | 0.8414 |
| 5.7149        | 7.0   | 805  | 9.3437          | 0.75     | 0.8328 |
| 5.7149        | 8.0   | 920  | 9.1808          | 0.7574   | 0.8254 |
| 1.0606        | 9.0   | 1035 | 8.2975          | 0.7941   | 0.8623 |
| 1.0606        | 10.0  | 1150 | 9.0654          | 0.7353   | 0.8151 |
| 1.0606        | 11.0  | 1265 | 9.3378          | 0.7623   | 0.8423 |
| 1.0606        | 12.0  | 1380 | 8.5584          | 0.7549   | 0.8227 |
| 1.0606        | 13.0  | 1495 | 9.8732          | 0.7451   | 0.8405 |
| 0.6339        | 14.0  | 1610 | 8.6408          | 0.7623   | 0.8336 |


### Framework versions

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