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# bert-large-uncased_crows_pairs_finetuned

This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the crows_pairs dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8687
- Accuracy: 0.7483

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7241        | 0.53  | 10   | 0.7015          | 0.4868   |
| 0.6975        | 1.05  | 20   | 0.7124          | 0.4934   |
| 0.6992        | 1.58  | 30   | 0.7102          | 0.4901   |
| 0.6941        | 2.11  | 40   | 0.6890          | 0.5430   |
| 0.665         | 2.63  | 50   | 0.6981          | 0.5464   |
| 0.5656        | 3.16  | 60   | 0.5434          | 0.7119   |
| 0.3695        | 3.68  | 70   | 0.7431          | 0.7152   |
| 0.3913        | 4.21  | 80   | 0.7834          | 0.7185   |
| 0.2617        | 4.74  | 90   | 0.6394          | 0.7318   |
| 0.1225        | 5.26  | 100  | 0.8882          | 0.6921   |
| 0.1549        | 5.79  | 110  | 0.8629          | 0.7119   |
| 0.1094        | 6.32  | 120  | 1.0113          | 0.7185   |
| 0.0418        | 6.84  | 130  | 1.2568          | 0.7219   |
| 0.023         | 7.37  | 140  | 1.3223          | 0.7417   |
| 0.045         | 7.89  | 150  | 1.5015          | 0.7086   |
| 0.0216        | 8.42  | 160  | 1.1833          | 0.7550   |
| 0.0084        | 8.95  | 170  | 1.4125          | 0.7318   |
| 0.0198        | 9.47  | 180  | 1.5301          | 0.7152   |
| 0.0061        | 10.0  | 190  | 1.3163          | 0.7483   |
| 0.0041        | 10.53 | 200  | 1.3083          | 0.7517   |
| 0.0046        | 11.05 | 210  | 1.4028          | 0.7616   |
| 0.0034        | 11.58 | 220  | 1.5256          | 0.7583   |
| 0.0012        | 12.11 | 230  | 1.6067          | 0.7583   |
| 0.001         | 12.63 | 240  | 1.6199          | 0.7649   |
| 0.005         | 13.16 | 250  | 1.7140          | 0.7384   |
| 0.0031        | 13.68 | 260  | 1.7680          | 0.7318   |
| 0.0008        | 14.21 | 270  | 1.7353          | 0.7252   |
| 0.0026        | 14.74 | 280  | 1.7242          | 0.7450   |
| 0.0013        | 15.26 | 290  | 1.7290          | 0.7483   |
| 0.0001        | 15.79 | 300  | 1.7421          | 0.7450   |
| 0.0008        | 16.32 | 310  | 1.7536          | 0.7450   |
| 0.0013        | 16.84 | 320  | 1.7588          | 0.7483   |
| 0.0014        | 17.37 | 330  | 1.8153          | 0.7417   |
| 0.0025        | 17.89 | 340  | 1.8432          | 0.7450   |
| 0.0024        | 18.42 | 350  | 1.8597          | 0.7351   |
| 0.0022        | 18.95 | 360  | 1.8676          | 0.7384   |
| 0.0001        | 19.47 | 370  | 1.8602          | 0.7417   |
| 0.0032        | 20.0  | 380  | 1.8600          | 0.7450   |
| 0.0017        | 20.53 | 390  | 1.8576          | 0.7417   |
| 0.0022        | 21.05 | 400  | 1.8603          | 0.7417   |
| 0.0024        | 21.58 | 410  | 1.8649          | 0.7417   |
| 0.002         | 22.11 | 420  | 1.8704          | 0.7417   |
| 0.0008        | 22.63 | 430  | 1.8764          | 0.7417   |
| 0.0019        | 23.16 | 440  | 1.8914          | 0.7417   |
| 0.0015        | 23.68 | 450  | 1.9026          | 0.7384   |
| 0.0014        | 24.21 | 460  | 1.9146          | 0.7384   |
| 0.0017        | 24.74 | 470  | 1.9258          | 0.7384   |
| 0.0027        | 25.26 | 480  | 1.9280          | 0.7384   |
| 0.0027        | 25.79 | 490  | 1.9285          | 0.7384   |
| 0.001         | 26.32 | 500  | 1.9236          | 0.7384   |
| 0.0034        | 26.84 | 510  | 1.8905          | 0.7450   |
| 0.0013        | 27.37 | 520  | 1.8730          | 0.7417   |
| 0.0016        | 27.89 | 530  | 1.8687          | 0.7450   |
| 0.0007        | 28.42 | 540  | 1.8681          | 0.7483   |
| 0.0042        | 28.95 | 550  | 1.8683          | 0.7483   |
| 0.0009        | 29.47 | 560  | 1.8686          | 0.7483   |
| 0.0018        | 30.0  | 570  | 1.8687          | 0.7483   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["crows_pairs"], "metrics": ["accuracy"], "model-index": [{"name": "bert-large-uncased_crows_pairs_finetuned", "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": 0.7483443708609272, "name": "Accuracy"}]}]}]}
transformers pytorch bert text-classification generated_from_trainer dataset:crows_pairs license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #dataset-crows_pairs #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

bert-large-uncased\_crows\_pairs\_finetuned
===========================================


This model is a fine-tuned version of bert-large-uncased on the crows\_pairs dataset.
It achieves the following results on the evaluation set:


* Loss: 1.8687
* Accuracy: 0.7483


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



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1
* Datasets 2.10.1
* Tokenizers 0.13.2



### 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 ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #dataset-crows_pairs #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### 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 ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #dataset-crows_pairs #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
### 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### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1
* Datasets 2.10.1
* Tokenizers 0.13.2