
<!-- 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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "bert-large-uncased_winobias_finetuned", "results": []}]}
transformers pytorch bert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

bert-large-uncased\_winobias\_finetuned
=======================================


This model is a fine-tuned version of 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



### 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: 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 ### 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 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### 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 ### 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 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### 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### Framework versions


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