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---
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
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