---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- super_glue
metrics:
- accuracy
model-index:
- name: '20230830190813'
  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. -->

# 20230830190813

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: 0.7333
- Accuracy: 0.5141

## 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: 0.0003
- 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   | 340   | 0.7313          | 0.5204   |
| 0.7523        | 2.0   | 680   | 0.7285          | 0.5      |
| 0.7461        | 3.0   | 1020  | 0.7229          | 0.5063   |
| 0.7461        | 4.0   | 1360  | 0.7062          | 0.5784   |
| 0.7318        | 5.0   | 1700  | 0.7796          | 0.6034   |
| 0.7057        | 6.0   | 2040  | 0.8194          | 0.5831   |
| 0.7057        | 7.0   | 2380  | 0.7297          | 0.5      |
| 0.7178        | 8.0   | 2720  | 0.7423          | 0.5      |
| 0.7417        | 9.0   | 3060  | 0.7280          | 0.5      |
| 0.7417        | 10.0  | 3400  | 0.7606          | 0.5016   |
| 0.7399        | 11.0  | 3740  | 0.7346          | 0.5172   |
| 0.7334        | 12.0  | 4080  | 0.7411          | 0.5      |
| 0.7334        | 13.0  | 4420  | 0.7588          | 0.5      |
| 0.7332        | 14.0  | 4760  | 0.7427          | 0.4718   |
| 0.7345        | 15.0  | 5100  | 0.7317          | 0.5047   |
| 0.7345        | 16.0  | 5440  | 0.7394          | 0.5031   |
| 0.7308        | 17.0  | 5780  | 0.7445          | 0.5      |
| 0.7295        | 18.0  | 6120  | 0.7517          | 0.4718   |
| 0.7295        | 19.0  | 6460  | 0.7323          | 0.5016   |
| 0.728         | 20.0  | 6800  | 0.7320          | 0.5157   |
| 0.73          | 21.0  | 7140  | 0.7309          | 0.5172   |
| 0.73          | 22.0  | 7480  | 0.7434          | 0.4984   |
| 0.7304        | 23.0  | 7820  | 0.7366          | 0.5094   |
| 0.7298        | 24.0  | 8160  | 0.7334          | 0.5      |
| 0.7283        | 25.0  | 8500  | 0.7342          | 0.5125   |
| 0.7283        | 26.0  | 8840  | 0.7311          | 0.5047   |
| 0.7291        | 27.0  | 9180  | 0.7565          | 0.4702   |
| 0.7292        | 28.0  | 9520  | 0.7282          | 0.5031   |
| 0.7292        | 29.0  | 9860  | 0.7333          | 0.5016   |
| 0.7261        | 30.0  | 10200 | 0.7328          | 0.5125   |
| 0.7279        | 31.0  | 10540 | 0.7349          | 0.5125   |
| 0.7279        | 32.0  | 10880 | 0.7592          | 0.4702   |
| 0.7252        | 33.0  | 11220 | 0.7393          | 0.5094   |
| 0.7263        | 34.0  | 11560 | 0.7394          | 0.5047   |
| 0.7263        | 35.0  | 11900 | 0.7465          | 0.5016   |
| 0.7269        | 36.0  | 12240 | 0.7349          | 0.5141   |
| 0.7263        | 37.0  | 12580 | 0.7295          | 0.5047   |
| 0.7263        | 38.0  | 12920 | 0.7329          | 0.5172   |
| 0.728         | 39.0  | 13260 | 0.7401          | 0.5      |
| 0.7254        | 40.0  | 13600 | 0.7331          | 0.5157   |
| 0.7254        | 41.0  | 13940 | 0.7308          | 0.5172   |
| 0.7265        | 42.0  | 14280 | 0.7312          | 0.5172   |
| 0.7234        | 43.0  | 14620 | 0.7393          | 0.5      |
| 0.7234        | 44.0  | 14960 | 0.7392          | 0.5      |
| 0.7254        | 45.0  | 15300 | 0.7389          | 0.5      |
| 0.7225        | 46.0  | 15640 | 0.7312          | 0.5157   |
| 0.7225        | 47.0  | 15980 | 0.7335          | 0.5      |
| 0.7268        | 48.0  | 16320 | 0.7363          | 0.5016   |
| 0.7258        | 49.0  | 16660 | 0.7393          | 0.5031   |
| 0.7253        | 50.0  | 17000 | 0.7306          | 0.5047   |
| 0.7253        | 51.0  | 17340 | 0.7372          | 0.5094   |
| 0.7247        | 52.0  | 17680 | 0.7402          | 0.5      |
| 0.7248        | 53.0  | 18020 | 0.7355          | 0.5141   |
| 0.7248        | 54.0  | 18360 | 0.7369          | 0.5157   |
| 0.7237        | 55.0  | 18700 | 0.7320          | 0.5141   |
| 0.7226        | 56.0  | 19040 | 0.7366          | 0.5172   |
| 0.7226        | 57.0  | 19380 | 0.7315          | 0.5172   |
| 0.7238        | 58.0  | 19720 | 0.7388          | 0.5016   |
| 0.7228        | 59.0  | 20060 | 0.7347          | 0.5047   |
| 0.7228        | 60.0  | 20400 | 0.7313          | 0.5141   |
| 0.7245        | 61.0  | 20740 | 0.7330          | 0.5141   |
| 0.7222        | 62.0  | 21080 | 0.7350          | 0.5141   |
| 0.7222        | 63.0  | 21420 | 0.7314          | 0.5157   |
| 0.724         | 64.0  | 21760 | 0.7327          | 0.5141   |
| 0.7236        | 65.0  | 22100 | 0.7306          | 0.5172   |
| 0.7236        | 66.0  | 22440 | 0.7351          | 0.5141   |
| 0.7205        | 67.0  | 22780 | 0.7343          | 0.5125   |
| 0.7236        | 68.0  | 23120 | 0.7313          | 0.5157   |
| 0.7236        | 69.0  | 23460 | 0.7338          | 0.5172   |
| 0.7221        | 70.0  | 23800 | 0.7317          | 0.5157   |
| 0.7226        | 71.0  | 24140 | 0.7344          | 0.5141   |
| 0.7226        | 72.0  | 24480 | 0.7342          | 0.5157   |
| 0.7209        | 73.0  | 24820 | 0.7333          | 0.5157   |
| 0.7229        | 74.0  | 25160 | 0.7358          | 0.5141   |
| 0.7204        | 75.0  | 25500 | 0.7342          | 0.5157   |
| 0.7204        | 76.0  | 25840 | 0.7329          | 0.5157   |
| 0.7213        | 77.0  | 26180 | 0.7334          | 0.5141   |
| 0.7208        | 78.0  | 26520 | 0.7335          | 0.5141   |
| 0.7208        | 79.0  | 26860 | 0.7330          | 0.5141   |
| 0.7203        | 80.0  | 27200 | 0.7333          | 0.5141   |


### Framework versions

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