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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- crows_pairs
metrics:
- accuracy
base_model: bert-base-uncased
model-index:
- name: bert-base-uncased_crows_pairs_classifieronly
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: crows_pairs
type: crows_pairs
config: crows_pairs
split: test
args: crows_pairs
metrics:
- type: accuracy
value: 0.5364238410596026
name: Accuracy
---
<!-- 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-base-uncased_crows_pairs_classifieronly
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the crows_pairs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6924
- Accuracy: 0.5364
- Tp: 0.0066
- Tn: 0.5298
- Fp: 0.0033
- Fn: 0.4603
## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Tp | Tn | Fp | Fn |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|
| 0.7219 | 1.05 | 20 | 0.7045 | 0.5331 | 0.0 | 0.5331 | 0.0 | 0.4669 |
| 0.6962 | 2.11 | 40 | 0.6962 | 0.4669 | 0.4669 | 0.0 | 0.5331 | 0.0 |
| 0.6983 | 3.16 | 60 | 0.6925 | 0.5331 | 0.0 | 0.5331 | 0.0 | 0.4669 |
| 0.7018 | 4.21 | 80 | 0.6962 | 0.4669 | 0.4669 | 0.0 | 0.5331 | 0.0 |
| 0.6972 | 5.26 | 100 | 0.6915 | 0.5331 | 0.0 | 0.5331 | 0.0 | 0.4669 |
| 0.6964 | 6.32 | 120 | 0.6934 | 0.4801 | 0.1391 | 0.3411 | 0.1921 | 0.3278 |
| 0.6983 | 7.37 | 140 | 0.6940 | 0.4636 | 0.3709 | 0.0927 | 0.4404 | 0.0960 |
| 0.7025 | 8.42 | 160 | 0.6964 | 0.4669 | 0.4669 | 0.0 | 0.5331 | 0.0 |
| 0.6958 | 9.47 | 180 | 0.6919 | 0.5331 | 0.0 | 0.5331 | 0.0 | 0.4669 |
| 0.7079 | 10.53 | 200 | 0.7002 | 0.4669 | 0.4669 | 0.0 | 0.5331 | 0.0 |
| 0.7033 | 11.58 | 220 | 0.6915 | 0.5331 | 0.0 | 0.5331 | 0.0 | 0.4669 |
| 0.6932 | 12.63 | 240 | 0.6933 | 0.5 | 0.1060 | 0.3940 | 0.1391 | 0.3609 |
| 0.7075 | 13.68 | 260 | 0.6919 | 0.5331 | 0.0 | 0.5331 | 0.0 | 0.4669 |
| 0.695 | 14.74 | 280 | 0.6936 | 0.4371 | 0.1523 | 0.2848 | 0.2483 | 0.3146 |
| 0.7068 | 15.79 | 300 | 0.6916 | 0.5331 | 0.0 | 0.5331 | 0.0 | 0.4669 |
| 0.7007 | 16.84 | 320 | 0.6916 | 0.5331 | 0.0 | 0.5331 | 0.0 | 0.4669 |
| 0.7035 | 17.89 | 340 | 0.6961 | 0.4669 | 0.4669 | 0.0 | 0.5331 | 0.0 |
| 0.7002 | 18.95 | 360 | 0.6919 | 0.5331 | 0.0 | 0.5331 | 0.0 | 0.4669 |
| 0.6992 | 20.0 | 380 | 0.6930 | 0.5166 | 0.0331 | 0.4834 | 0.0497 | 0.4338 |
| 0.7024 | 21.05 | 400 | 0.6924 | 0.5364 | 0.0066 | 0.5298 | 0.0033 | 0.4603 |
| 0.694 | 22.11 | 420 | 0.6949 | 0.4669 | 0.4603 | 0.0066 | 0.5265 | 0.0066 |
| 0.7085 | 23.16 | 440 | 0.6928 | 0.5265 | 0.0199 | 0.5066 | 0.0265 | 0.4470 |
| 0.6999 | 24.21 | 460 | 0.6936 | 0.4338 | 0.1457 | 0.2881 | 0.2450 | 0.3212 |
| 0.6926 | 25.26 | 480 | 0.6921 | 0.5331 | 0.0033 | 0.5298 | 0.0033 | 0.4636 |
| 0.7088 | 26.32 | 500 | 0.6923 | 0.5331 | 0.0033 | 0.5298 | 0.0033 | 0.4636 |
| 0.6932 | 27.37 | 520 | 0.6922 | 0.5331 | 0.0033 | 0.5298 | 0.0033 | 0.4636 |
| 0.7011 | 28.42 | 540 | 0.6925 | 0.5364 | 0.0066 | 0.5298 | 0.0033 | 0.4603 |
| 0.7016 | 29.47 | 560 | 0.6923 | 0.5331 | 0.0033 | 0.5298 | 0.0033 | 0.4636 |
| 0.7015 | 30.53 | 580 | 0.6925 | 0.5364 | 0.0099 | 0.5265 | 0.0066 | 0.4570 |
| 0.7002 | 31.58 | 600 | 0.6929 | 0.5232 | 0.0331 | 0.4901 | 0.0430 | 0.4338 |
| 0.701 | 32.63 | 620 | 0.6932 | 0.5099 | 0.0563 | 0.4536 | 0.0795 | 0.4106 |
| 0.693 | 33.68 | 640 | 0.6921 | 0.5331 | 0.0 | 0.5331 | 0.0 | 0.4669 |
| 0.711 | 34.74 | 660 | 0.6925 | 0.5364 | 0.0099 | 0.5265 | 0.0066 | 0.4570 |
| 0.7013 | 35.79 | 680 | 0.6924 | 0.5331 | 0.0033 | 0.5298 | 0.0033 | 0.4636 |
| 0.6975 | 36.84 | 700 | 0.6916 | 0.5331 | 0.0 | 0.5331 | 0.0 | 0.4669 |
| 0.7035 | 37.89 | 720 | 0.6918 | 0.5331 | 0.0 | 0.5331 | 0.0 | 0.4669 |
| 0.6991 | 38.95 | 740 | 0.6929 | 0.5232 | 0.0298 | 0.4934 | 0.0397 | 0.4371 |
| 0.7165 | 40.0 | 760 | 0.6923 | 0.5331 | 0.0033 | 0.5298 | 0.0033 | 0.4636 |
| 0.7029 | 41.05 | 780 | 0.6931 | 0.5066 | 0.0464 | 0.4603 | 0.0728 | 0.4205 |
| 0.7021 | 42.11 | 800 | 0.6923 | 0.5331 | 0.0033 | 0.5298 | 0.0033 | 0.4636 |
| 0.6993 | 43.16 | 820 | 0.6935 | 0.4934 | 0.1291 | 0.3642 | 0.1689 | 0.3377 |
| 0.7 | 44.21 | 840 | 0.6926 | 0.5331 | 0.0132 | 0.5199 | 0.0132 | 0.4536 |
| 0.7023 | 45.26 | 860 | 0.6926 | 0.5331 | 0.0099 | 0.5232 | 0.0099 | 0.4570 |
| 0.6961 | 46.32 | 880 | 0.6927 | 0.5232 | 0.0132 | 0.5099 | 0.0232 | 0.4536 |
| 0.7014 | 47.37 | 900 | 0.6923 | 0.5331 | 0.0033 | 0.5298 | 0.0033 | 0.4636 |
| 0.7025 | 48.42 | 920 | 0.6924 | 0.5331 | 0.0033 | 0.5298 | 0.0033 | 0.4636 |
| 0.702 | 49.47 | 940 | 0.6924 | 0.5364 | 0.0066 | 0.5298 | 0.0033 | 0.4603 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2
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