---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert-base-uncased-finetuned-CLS-RTE
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: glue
      type: glue
      config: rte
      split: validation
      args: rte
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6967509025270758
---

<!-- 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. -->

# bert-base-uncased-finetuned-CLS-RTE

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2843
- Accuracy: 0.6968

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 156  | 0.6285          | 0.6390   |
| No log        | 2.0   | 312  | 0.6483          | 0.6679   |
| No log        | 3.0   | 468  | 0.8430          | 0.7004   |
| 0.4504        | 4.0   | 624  | 1.2886          | 0.6606   |
| 0.4504        | 5.0   | 780  | 1.6445          | 0.7004   |
| 0.4504        | 6.0   | 936  | 1.8099          | 0.6751   |
| 0.0631        | 7.0   | 1092 | 1.8173          | 0.7040   |
| 0.0631        | 8.0   | 1248 | 1.9799          | 0.7004   |
| 0.0631        | 9.0   | 1404 | 1.9767          | 0.6968   |
| 0.0159        | 10.0  | 1560 | 2.1696          | 0.6715   |
| 0.0159        | 11.0  | 1716 | 2.2142          | 0.6859   |
| 0.0159        | 12.0  | 1872 | 2.2605          | 0.6823   |
| 0.0076        | 13.0  | 2028 | 2.2775          | 0.7040   |
| 0.0076        | 14.0  | 2184 | 2.2719          | 0.6968   |
| 0.0076        | 15.0  | 2340 | 2.2843          | 0.6968   |


### Framework versions

- Transformers 4.36.1
- Pytorch 2.1.2
- Datasets 2.15.0
- Tokenizers 0.15.0