---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- super_glue
metrics:
- accuracy
model-index:
- name: '20230826065732'
  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. -->

# 20230826065732

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: 0.5294
- Accuracy: 0.67

## 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: 0.02
- 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: 80.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 25   | 0.6448          | 0.4      |
| No log        | 2.0   | 50   | 0.7950          | 0.65     |
| No log        | 3.0   | 75   | 0.6181          | 0.54     |
| No log        | 4.0   | 100  | 0.5601          | 0.6      |
| No log        | 5.0   | 125  | 0.5816          | 0.42     |
| No log        | 6.0   | 150  | 0.5957          | 0.43     |
| No log        | 7.0   | 175  | 0.5331          | 0.61     |
| No log        | 8.0   | 200  | 0.5507          | 0.61     |
| No log        | 9.0   | 225  | 0.5438          | 0.62     |
| No log        | 10.0  | 250  | 0.5455          | 0.65     |
| No log        | 11.0  | 275  | 0.5141          | 0.65     |
| No log        | 12.0  | 300  | 0.5019          | 0.71     |
| No log        | 13.0  | 325  | 0.6824          | 0.7      |
| No log        | 14.0  | 350  | 0.5735          | 0.73     |
| No log        | 15.0  | 375  | 0.5578          | 0.69     |
| No log        | 16.0  | 400  | 0.5607          | 0.72     |
| No log        | 17.0  | 425  | 0.5974          | 0.71     |
| No log        | 18.0  | 450  | 0.8102          | 0.71     |
| No log        | 19.0  | 475  | 0.6757          | 0.73     |
| 0.7598        | 20.0  | 500  | 0.5266          | 0.74     |
| 0.7598        | 21.0  | 525  | 0.6271          | 0.69     |
| 0.7598        | 22.0  | 550  | 0.6341          | 0.7      |
| 0.7598        | 23.0  | 575  | 0.6874          | 0.7      |
| 0.7598        | 24.0  | 600  | 0.5264          | 0.72     |
| 0.7598        | 25.0  | 625  | 0.5148          | 0.73     |
| 0.7598        | 26.0  | 650  | 0.5760          | 0.77     |
| 0.7598        | 27.0  | 675  | 0.6581          | 0.71     |
| 0.7598        | 28.0  | 700  | 0.6479          | 0.71     |
| 0.7598        | 29.0  | 725  | 0.6960          | 0.69     |
| 0.7598        | 30.0  | 750  | 0.6919          | 0.7      |
| 0.7598        | 31.0  | 775  | 0.6421          | 0.68     |
| 0.7598        | 32.0  | 800  | 0.5681          | 0.68     |
| 0.7598        | 33.0  | 825  | 0.5631          | 0.68     |
| 0.7598        | 34.0  | 850  | 0.5676          | 0.66     |
| 0.7598        | 35.0  | 875  | 0.5389          | 0.68     |
| 0.7598        | 36.0  | 900  | 0.6267          | 0.68     |
| 0.7598        | 37.0  | 925  | 0.6107          | 0.65     |
| 0.7598        | 38.0  | 950  | 0.5359          | 0.66     |
| 0.7598        | 39.0  | 975  | 0.5741          | 0.67     |
| 0.4266        | 40.0  | 1000 | 0.5928          | 0.69     |
| 0.4266        | 41.0  | 1025 | 0.5307          | 0.68     |
| 0.4266        | 42.0  | 1050 | 0.5909          | 0.66     |
| 0.4266        | 43.0  | 1075 | 0.5733          | 0.66     |
| 0.4266        | 44.0  | 1100 | 0.5561          | 0.66     |
| 0.4266        | 45.0  | 1125 | 0.5600          | 0.69     |
| 0.4266        | 46.0  | 1150 | 0.5228          | 0.66     |
| 0.4266        | 47.0  | 1175 | 0.5383          | 0.7      |
| 0.4266        | 48.0  | 1200 | 0.5643          | 0.69     |
| 0.4266        | 49.0  | 1225 | 0.5493          | 0.7      |
| 0.4266        | 50.0  | 1250 | 0.5576          | 0.7      |
| 0.4266        | 51.0  | 1275 | 0.5543          | 0.68     |
| 0.4266        | 52.0  | 1300 | 0.5615          | 0.69     |
| 0.4266        | 53.0  | 1325 | 0.5358          | 0.67     |
| 0.4266        | 54.0  | 1350 | 0.5405          | 0.69     |
| 0.4266        | 55.0  | 1375 | 0.5327          | 0.69     |
| 0.4266        | 56.0  | 1400 | 0.5645          | 0.67     |
| 0.4266        | 57.0  | 1425 | 0.5240          | 0.67     |
| 0.4266        | 58.0  | 1450 | 0.5402          | 0.67     |
| 0.4266        | 59.0  | 1475 | 0.5495          | 0.68     |
| 0.3249        | 60.0  | 1500 | 0.5624          | 0.66     |
| 0.3249        | 61.0  | 1525 | 0.5513          | 0.67     |
| 0.3249        | 62.0  | 1550 | 0.5537          | 0.68     |
| 0.3249        | 63.0  | 1575 | 0.5444          | 0.68     |
| 0.3249        | 64.0  | 1600 | 0.5553          | 0.68     |
| 0.3249        | 65.0  | 1625 | 0.5221          | 0.68     |
| 0.3249        | 66.0  | 1650 | 0.5136          | 0.68     |
| 0.3249        | 67.0  | 1675 | 0.5231          | 0.69     |
| 0.3249        | 68.0  | 1700 | 0.5305          | 0.69     |
| 0.3249        | 69.0  | 1725 | 0.5278          | 0.68     |
| 0.3249        | 70.0  | 1750 | 0.5440          | 0.66     |
| 0.3249        | 71.0  | 1775 | 0.5411          | 0.67     |
| 0.3249        | 72.0  | 1800 | 0.5346          | 0.69     |
| 0.3249        | 73.0  | 1825 | 0.5241          | 0.67     |
| 0.3249        | 74.0  | 1850 | 0.5425          | 0.67     |
| 0.3249        | 75.0  | 1875 | 0.5213          | 0.67     |
| 0.3249        | 76.0  | 1900 | 0.5405          | 0.66     |
| 0.3249        | 77.0  | 1925 | 0.5251          | 0.67     |
| 0.3249        | 78.0  | 1950 | 0.5300          | 0.67     |
| 0.3249        | 79.0  | 1975 | 0.5285          | 0.67     |
| 0.2946        | 80.0  | 2000 | 0.5294          | 0.67     |


### Framework versions

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