---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- super_glue
metrics:
- accuracy
model-index:
- name: '20230823013619'
  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. -->

# 20230823013619

This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on the super_glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0007
- Accuracy: 0.4729

## 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: 0.003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 11
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 60.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 156  | 0.0076          | 0.5199   |
| No log        | 2.0   | 312  | 0.0418          | 0.5343   |
| No log        | 3.0   | 468  | 0.0044          | 0.5054   |
| 0.0669        | 4.0   | 624  | 0.0117          | 0.4693   |
| 0.0669        | 5.0   | 780  | 0.0333          | 0.4729   |
| 0.0669        | 6.0   | 936  | 0.0014          | 0.4693   |
| 0.0209        | 7.0   | 1092 | 0.0008          | 0.4729   |
| 0.0209        | 8.0   | 1248 | 0.0031          | 0.4729   |
| 0.0209        | 9.0   | 1404 | 0.0049          | 0.4982   |
| 0.0144        | 10.0  | 1560 | 0.0007          | 0.4729   |
| 0.0144        | 11.0  | 1716 | 0.0014          | 0.4693   |
| 0.0144        | 12.0  | 1872 | 0.0022          | 0.5054   |
| 0.0094        | 13.0  | 2028 | 0.0008          | 0.4729   |
| 0.0094        | 14.0  | 2184 | 0.0012          | 0.4729   |
| 0.0094        | 15.0  | 2340 | 0.0018          | 0.4729   |
| 0.0094        | 16.0  | 2496 | 0.0008          | 0.4729   |
| 0.0087        | 17.0  | 2652 | 0.0011          | 0.4729   |
| 0.0087        | 18.0  | 2808 | 0.0009          | 0.4729   |
| 0.0087        | 19.0  | 2964 | 0.0010          | 0.4729   |
| 0.0091        | 20.0  | 3120 | 0.0021          | 0.4585   |
| 0.0091        | 21.0  | 3276 | 0.0008          | 0.4729   |
| 0.0091        | 22.0  | 3432 | 0.0010          | 0.4729   |
| 0.0087        | 23.0  | 3588 | 0.0007          | 0.4729   |
| 0.0087        | 24.0  | 3744 | 0.0012          | 0.4765   |
| 0.0087        | 25.0  | 3900 | 0.0013          | 0.4729   |
| 0.0088        | 26.0  | 4056 | 0.0010          | 0.4910   |
| 0.0088        | 27.0  | 4212 | 0.0012          | 0.4765   |
| 0.0088        | 28.0  | 4368 | 0.0012          | 0.4729   |
| 0.0087        | 29.0  | 4524 | 0.0013          | 0.4910   |
| 0.0087        | 30.0  | 4680 | 0.0009          | 0.4729   |
| 0.0087        | 31.0  | 4836 | 0.0012          | 0.4729   |
| 0.0087        | 32.0  | 4992 | 0.0007          | 0.4729   |
| 0.0089        | 33.0  | 5148 | 0.0009          | 0.4729   |
| 0.0089        | 34.0  | 5304 | 0.0008          | 0.4729   |
| 0.0089        | 35.0  | 5460 | 0.0007          | 0.4729   |
| 0.0087        | 36.0  | 5616 | 0.0009          | 0.4729   |
| 0.0087        | 37.0  | 5772 | 0.0007          | 0.4801   |
| 0.0087        | 38.0  | 5928 | 0.0007          | 0.4729   |
| 0.0093        | 39.0  | 6084 | 0.0007          | 0.4729   |
| 0.0093        | 40.0  | 6240 | 0.0008          | 0.4729   |
| 0.0093        | 41.0  | 6396 | 0.0011          | 0.4729   |
| 0.0086        | 42.0  | 6552 | 0.0008          | 0.4729   |
| 0.0086        | 43.0  | 6708 | 0.0017          | 0.4729   |
| 0.0086        | 44.0  | 6864 | 0.0009          | 0.4729   |
| 0.0085        | 45.0  | 7020 | 0.0007          | 0.4729   |
| 0.0085        | 46.0  | 7176 | 0.0022          | 0.4729   |
| 0.0085        | 47.0  | 7332 | 0.0009          | 0.4729   |
| 0.0085        | 48.0  | 7488 | 0.0008          | 0.4729   |
| 0.0087        | 49.0  | 7644 | 0.0007          | 0.4729   |
| 0.0087        | 50.0  | 7800 | 0.0010          | 0.4729   |
| 0.0087        | 51.0  | 7956 | 0.0007          | 0.4729   |
| 0.0084        | 52.0  | 8112 | 0.0013          | 0.4729   |
| 0.0084        | 53.0  | 8268 | 0.0010          | 0.4729   |
| 0.0084        | 54.0  | 8424 | 0.0010          | 0.4729   |
| 0.0083        | 55.0  | 8580 | 0.0007          | 0.4729   |
| 0.0083        | 56.0  | 8736 | 0.0007          | 0.4729   |
| 0.0083        | 57.0  | 8892 | 0.0007          | 0.4729   |
| 0.0082        | 58.0  | 9048 | 0.0007          | 0.4729   |
| 0.0082        | 59.0  | 9204 | 0.0007          | 0.4729   |
| 0.0082        | 60.0  | 9360 | 0.0007          | 0.4729   |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3