File size: 6,312 Bytes
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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: 0.5
---
<!-- 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: 0.6933
- Accuracy: 0.5
- Tp: 0.5
- Tn: 0.0
- Fp: 0.5
- Fn: 0.0
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|
| 0.7406 | 1.05 | 20 | 0.6941 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
| 0.7008 | 2.11 | 40 | 0.6959 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
| 0.7067 | 3.16 | 60 | 0.6932 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
| 0.7029 | 4.21 | 80 | 0.6937 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
| 0.7103 | 5.26 | 100 | 0.6932 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
| 0.7085 | 6.32 | 120 | 0.7004 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
| 0.7061 | 7.37 | 140 | 0.6933 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
| 0.7013 | 8.42 | 160 | 0.6954 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
| 0.6952 | 9.47 | 180 | 0.6933 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
| 0.7084 | 10.53 | 200 | 0.7079 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
| 0.71 | 11.58 | 220 | 0.6999 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
| 0.7036 | 12.63 | 240 | 0.6932 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
| 0.7043 | 13.68 | 260 | 0.6942 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
| 0.7058 | 14.74 | 280 | 0.6947 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
| 0.6993 | 15.79 | 300 | 0.6951 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
| 0.7009 | 16.84 | 320 | 0.6936 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
| 0.7069 | 17.89 | 340 | 0.7002 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
| 0.7068 | 18.95 | 360 | 0.6970 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
| 0.7042 | 20.0 | 380 | 0.6935 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
| 0.6999 | 21.05 | 400 | 0.6957 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
| 0.6966 | 22.11 | 420 | 0.6936 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
| 0.6975 | 23.16 | 440 | 0.6934 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
| 0.7043 | 24.21 | 460 | 0.6934 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
| 0.7002 | 25.26 | 480 | 0.6932 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
| 0.7039 | 26.32 | 500 | 0.7004 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
| 0.6927 | 27.37 | 520 | 0.6932 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
| 0.7078 | 28.42 | 540 | 0.6941 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
| 0.6999 | 29.47 | 560 | 0.6969 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
| 0.7063 | 30.53 | 580 | 0.6936 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
| 0.7011 | 31.58 | 600 | 0.6934 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
| 0.7061 | 32.63 | 620 | 0.6958 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
| 0.6971 | 33.68 | 640 | 0.6932 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
| 0.7007 | 34.74 | 660 | 0.6932 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
| 0.7014 | 35.79 | 680 | 0.6954 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
| 0.6976 | 36.84 | 700 | 0.6951 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
| 0.6957 | 37.89 | 720 | 0.6936 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
| 0.7009 | 38.95 | 740 | 0.6950 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
| 0.6941 | 40.0 | 760 | 0.6933 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
| 0.6989 | 41.05 | 780 | 0.6948 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
| 0.6935 | 42.11 | 800 | 0.6974 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
| 0.6939 | 43.16 | 820 | 0.6956 | 0.5 | 0.0 | 0.5 | 0.0 | 0.5 |
| 0.6975 | 44.21 | 840 | 0.6955 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
| 0.669 | 45.26 | 860 | 0.7089 | 0.5132 | 0.1623 | 0.3510 | 0.1490 | 0.3377 |
| 0.6896 | 46.32 | 880 | 0.7088 | 0.4669 | 0.4106 | 0.0563 | 0.4437 | 0.0894 |
| 0.6942 | 47.37 | 900 | 0.6944 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
| 0.6942 | 48.42 | 920 | 0.6933 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
| 0.6921 | 49.47 | 940 | 0.6933 | 0.5 | 0.5 | 0.0 | 0.5 | 0.0 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2
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