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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-large-uncased_winobias_finetuned
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. -->
# bert-large-uncased_winobias_finetuned
This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4783
- Accuracy: 0.7986
## 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: 1e-05
- train_batch_size: 128
- eval_batch_size: 64
- 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 | 0.38 | 5 | 0.7011 | 0.4994 |
| No log | 0.77 | 10 | 0.6942 | 0.4987 |
| No log | 1.15 | 15 | 0.6941 | 0.5063 |
| No log | 1.54 | 20 | 0.6936 | 0.4924 |
| No log | 1.92 | 25 | 0.6928 | 0.5114 |
| No log | 2.31 | 30 | 0.6925 | 0.5196 |
| No log | 2.69 | 35 | 0.6925 | 0.5215 |
| No log | 3.08 | 40 | 0.6923 | 0.5227 |
| No log | 3.46 | 45 | 0.6922 | 0.5259 |
| No log | 3.85 | 50 | 0.6922 | 0.5202 |
| No log | 4.23 | 55 | 0.6918 | 0.5316 |
| No log | 4.62 | 60 | 0.6912 | 0.5499 |
| No log | 5.0 | 65 | 0.6904 | 0.5574 |
| No log | 5.38 | 70 | 0.6899 | 0.5492 |
| No log | 5.77 | 75 | 0.6894 | 0.5417 |
| No log | 6.15 | 80 | 0.6890 | 0.5290 |
| No log | 6.54 | 85 | 0.6883 | 0.5366 |
| No log | 6.92 | 90 | 0.6863 | 0.5726 |
| No log | 7.31 | 95 | 0.6837 | 0.5909 |
| No log | 7.69 | 100 | 0.6812 | 0.5890 |
| No log | 8.08 | 105 | 0.6788 | 0.5915 |
| No log | 8.46 | 110 | 0.6738 | 0.6225 |
| No log | 8.85 | 115 | 0.6685 | 0.6503 |
| No log | 9.23 | 120 | 0.6616 | 0.6698 |
| No log | 9.62 | 125 | 0.6533 | 0.6799 |
| No log | 10.0 | 130 | 0.6403 | 0.7027 |
| No log | 10.38 | 135 | 0.6282 | 0.7077 |
| No log | 10.77 | 140 | 0.6142 | 0.7235 |
| No log | 11.15 | 145 | 0.5967 | 0.7355 |
| No log | 11.54 | 150 | 0.5814 | 0.7437 |
| No log | 11.92 | 155 | 0.5662 | 0.7513 |
| No log | 12.31 | 160 | 0.5454 | 0.7607 |
| No log | 12.69 | 165 | 0.5251 | 0.7771 |
| No log | 13.08 | 170 | 0.5091 | 0.7872 |
| No log | 13.46 | 175 | 0.4975 | 0.7942 |
| No log | 13.85 | 180 | 0.4892 | 0.7967 |
| No log | 14.23 | 185 | 0.4832 | 0.7992 |
| No log | 14.62 | 190 | 0.4797 | 0.8005 |
| No log | 15.0 | 195 | 0.4783 | 0.7986 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2
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