---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-large-uncased_winobias_classifieronly
  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_classifieronly

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: 0.6934
- Accuracy: 0.5095

## 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    | 0.8249          | 0.4987   |
| No log        | 0.77  | 10   | 0.8058          | 0.4987   |
| No log        | 1.15  | 15   | 0.7886          | 0.4987   |
| No log        | 1.54  | 20   | 0.7731          | 0.4987   |
| No log        | 1.92  | 25   | 0.7593          | 0.4981   |
| No log        | 2.31  | 30   | 0.7470          | 0.4987   |
| No log        | 2.69  | 35   | 0.7363          | 0.4994   |
| No log        | 3.08  | 40   | 0.7276          | 0.4994   |
| No log        | 3.46  | 45   | 0.7205          | 0.4994   |
| No log        | 3.85  | 50   | 0.7142          | 0.5      |
| No log        | 4.23  | 55   | 0.7088          | 0.5      |
| No log        | 4.62  | 60   | 0.7044          | 0.4994   |
| No log        | 5.0   | 65   | 0.7009          | 0.5      |
| No log        | 5.38  | 70   | 0.6983          | 0.5013   |
| No log        | 5.77  | 75   | 0.6966          | 0.5006   |
| No log        | 6.15  | 80   | 0.6955          | 0.4994   |
| No log        | 6.54  | 85   | 0.6948          | 0.5032   |
| No log        | 6.92  | 90   | 0.6943          | 0.5158   |
| No log        | 7.31  | 95   | 0.6940          | 0.5114   |
| No log        | 7.69  | 100  | 0.6938          | 0.5120   |
| No log        | 8.08  | 105  | 0.6936          | 0.5088   |
| No log        | 8.46  | 110  | 0.6936          | 0.5101   |
| No log        | 8.85  | 115  | 0.6935          | 0.5101   |
| No log        | 9.23  | 120  | 0.6935          | 0.5107   |
| No log        | 9.62  | 125  | 0.6934          | 0.5120   |
| No log        | 10.0  | 130  | 0.6934          | 0.5107   |
| No log        | 10.38 | 135  | 0.6934          | 0.5126   |
| No log        | 10.77 | 140  | 0.6934          | 0.5133   |
| No log        | 11.15 | 145  | 0.6934          | 0.5139   |
| No log        | 11.54 | 150  | 0.6934          | 0.5114   |
| No log        | 11.92 | 155  | 0.6934          | 0.5088   |
| No log        | 12.31 | 160  | 0.6934          | 0.5076   |
| No log        | 12.69 | 165  | 0.6934          | 0.5063   |
| No log        | 13.08 | 170  | 0.6934          | 0.5101   |
| No log        | 13.46 | 175  | 0.6934          | 0.5107   |
| No log        | 13.85 | 180  | 0.6934          | 0.5101   |
| No log        | 14.23 | 185  | 0.6934          | 0.5095   |
| No log        | 14.62 | 190  | 0.6934          | 0.5095   |
| No log        | 15.0  | 195  | 0.6934          | 0.5095   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2