|
--- |
|
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 |
|
|
