| --- |
| 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 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.26.1 |
| - Pytorch 1.13.1 |
| - Datasets 2.10.1 |
| - Tokenizers 0.13.2 |
|
|
