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---
license: mit
tags:
- generated_from_trainer
datasets:
- crows_pairs
metrics:
- accuracy
model-index:
- name: xlnet-base-cased_crows_pairs_finetuned
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: crows_pairs
type: crows_pairs
config: crows_pairs
split: test
args: crows_pairs
metrics:
- name: Accuracy
type: accuracy
value: 0.7119205298013245
---
<!-- 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. -->
# xlnet-base-cased_crows_pairs_finetuned
This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on the crows_pairs dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5652
- Accuracy: 0.7119
## 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: 5e-05
- 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: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.728 | 0.53 | 10 | 0.6939 | 0.4901 |
| 0.6914 | 1.05 | 20 | 0.6939 | 0.4901 |
| 0.705 | 1.58 | 30 | 0.6925 | 0.5066 |
| 0.6993 | 2.11 | 40 | 0.6949 | 0.5066 |
| 0.6979 | 2.63 | 50 | 0.6996 | 0.5066 |
| 0.7152 | 3.16 | 60 | 0.6940 | 0.4901 |
| 0.7158 | 3.68 | 70 | 0.7007 | 0.4934 |
| 0.6968 | 4.21 | 80 | 0.6999 | 0.5066 |
| 0.7164 | 4.74 | 90 | 0.6977 | 0.4934 |
| 0.6698 | 5.26 | 100 | 0.7079 | 0.4536 |
| 0.611 | 5.79 | 110 | 0.8882 | 0.5099 |
| 0.6487 | 6.32 | 120 | 0.8360 | 0.5066 |
| 0.5223 | 6.84 | 130 | 0.8047 | 0.5728 |
| 0.2879 | 7.37 | 140 | 1.1483 | 0.5795 |
| 0.2369 | 7.89 | 150 | 1.1773 | 0.5993 |
| 0.2542 | 8.42 | 160 | 0.9170 | 0.6424 |
| 0.1743 | 8.95 | 170 | 1.3674 | 0.6424 |
| 0.1307 | 9.47 | 180 | 1.0740 | 0.7152 |
| 0.0718 | 10.0 | 190 | 1.4397 | 0.6424 |
| 0.0278 | 10.53 | 200 | 1.9821 | 0.6523 |
| 0.0519 | 11.05 | 210 | 1.6970 | 0.6755 |
| 0.0269 | 11.58 | 220 | 1.8299 | 0.6656 |
| 0.0556 | 12.11 | 230 | 1.9459 | 0.7086 |
| 0.0455 | 12.63 | 240 | 1.6443 | 0.6854 |
| 0.0665 | 13.16 | 250 | 1.9887 | 0.6821 |
| 0.009 | 13.68 | 260 | 2.0236 | 0.6788 |
| 0.0146 | 14.21 | 270 | 1.8515 | 0.7152 |
| 0.0034 | 14.74 | 280 | 1.9315 | 0.7252 |
| 0.0248 | 15.26 | 290 | 2.0754 | 0.7119 |
| 0.0536 | 15.79 | 300 | 2.0371 | 0.7053 |
| 0.0393 | 16.32 | 310 | 1.9381 | 0.6987 |
| 0.0255 | 16.84 | 320 | 1.9074 | 0.6788 |
| 0.0116 | 17.37 | 330 | 2.2182 | 0.6623 |
| 0.0128 | 17.89 | 340 | 2.3002 | 0.6689 |
| 0.0006 | 18.42 | 350 | 2.2353 | 0.6788 |
| 0.0053 | 18.95 | 360 | 2.4277 | 0.6755 |
| 0.0013 | 19.47 | 370 | 2.5156 | 0.6490 |
| 0.0004 | 20.0 | 380 | 2.5091 | 0.6689 |
| 0.0003 | 20.53 | 390 | 2.4096 | 0.6854 |
| 0.0017 | 21.05 | 400 | 2.3497 | 0.6921 |
| 0.0001 | 21.58 | 410 | 2.3376 | 0.6854 |
| 0.012 | 22.11 | 420 | 2.3832 | 0.6854 |
| 0.0002 | 22.63 | 430 | 2.4388 | 0.7053 |
| 0.0001 | 23.16 | 440 | 2.4821 | 0.7152 |
| 0.0001 | 23.68 | 450 | 2.5027 | 0.7119 |
| 0.0001 | 24.21 | 460 | 2.5105 | 0.7152 |
| 0.0001 | 24.74 | 470 | 2.5145 | 0.7152 |
| 0.0002 | 25.26 | 480 | 2.5143 | 0.6954 |
| 0.0001 | 25.79 | 490 | 2.5629 | 0.6821 |
| 0.0002 | 26.32 | 500 | 2.5414 | 0.6887 |
| 0.0001 | 26.84 | 510 | 2.5301 | 0.7119 |
| 0.0012 | 27.37 | 520 | 2.5360 | 0.7020 |
| 0.0 | 27.89 | 530 | 2.5428 | 0.6921 |
| 0.0117 | 28.42 | 540 | 2.5455 | 0.6954 |
| 0.0001 | 28.95 | 550 | 2.5598 | 0.7086 |
| 0.0001 | 29.47 | 560 | 2.5648 | 0.7119 |
| 0.0001 | 30.0 | 570 | 2.5652 | 0.7119 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2
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