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# bert-large-uncased_stereoset_finetuned

This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the stereoset dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0729
- Accuracy: 0.7716

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.21  | 5    | 0.6925          | 0.5071   |
| No log        | 0.42  | 10   | 0.6978          | 0.5008   |
| No log        | 0.62  | 15   | 0.6891          | 0.5275   |
| No log        | 0.83  | 20   | 0.6850          | 0.5487   |
| No log        | 1.04  | 25   | 0.7521          | 0.5126   |
| No log        | 1.25  | 30   | 0.6577          | 0.6177   |
| No log        | 1.46  | 35   | 0.6759          | 0.5440   |
| No log        | 1.67  | 40   | 0.6395          | 0.6405   |
| No log        | 1.88  | 45   | 0.6064          | 0.6719   |
| No log        | 2.08  | 50   | 0.5822          | 0.6986   |
| No log        | 2.29  | 55   | 0.5566          | 0.7096   |
| No log        | 2.5   | 60   | 0.5411          | 0.7331   |
| No log        | 2.71  | 65   | 0.5448          | 0.7551   |
| No log        | 2.92  | 70   | 0.5384          | 0.7339   |
| No log        | 3.12  | 75   | 0.5487          | 0.7535   |
| No log        | 3.33  | 80   | 0.5572          | 0.7567   |
| No log        | 3.54  | 85   | 0.5763          | 0.7614   |
| No log        | 3.75  | 90   | 0.5756          | 0.7645   |
| No log        | 3.96  | 95   | 0.5524          | 0.7645   |
| No log        | 4.17  | 100  | 0.6320          | 0.7614   |
| No log        | 4.38  | 105  | 0.6512          | 0.7575   |
| No log        | 4.58  | 110  | 0.6582          | 0.7606   |
| No log        | 4.79  | 115  | 0.6731          | 0.7669   |
| No log        | 5.0   | 120  | 0.6944          | 0.7575   |
| No log        | 5.21  | 125  | 0.7142          | 0.7575   |
| No log        | 5.42  | 130  | 0.7004          | 0.7645   |
| No log        | 5.62  | 135  | 0.6794          | 0.7630   |
| No log        | 5.83  | 140  | 0.7108          | 0.7606   |
| No log        | 6.04  | 145  | 0.7730          | 0.7590   |
| No log        | 6.25  | 150  | 0.8083          | 0.7614   |
| No log        | 6.46  | 155  | 0.8361          | 0.7653   |
| No log        | 6.67  | 160  | 0.8498          | 0.7692   |
| No log        | 6.88  | 165  | 0.8769          | 0.7700   |
| No log        | 7.08  | 170  | 0.8324          | 0.7582   |
| No log        | 7.29  | 175  | 0.7945          | 0.7645   |
| No log        | 7.5   | 180  | 0.8480          | 0.7684   |
| No log        | 7.71  | 185  | 0.8905          | 0.7724   |
| No log        | 7.92  | 190  | 0.9560          | 0.7700   |
| No log        | 8.12  | 195  | 0.9976          | 0.7669   |
| No log        | 8.33  | 200  | 1.0315          | 0.7677   |
| No log        | 8.54  | 205  | 1.0413          | 0.7692   |
| No log        | 8.75  | 210  | 1.0216          | 0.7708   |
| No log        | 8.96  | 215  | 1.0251          | 0.7716   |
| No log        | 9.17  | 220  | 1.0483          | 0.7716   |
| No log        | 9.38  | 225  | 1.0616          | 0.7716   |
| No log        | 9.58  | 230  | 1.0703          | 0.7708   |
| No log        | 9.79  | 235  | 1.0731          | 0.7732   |
| No log        | 10.0  | 240  | 1.0729          | 0.7716   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1
- Datasets 2.9.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["stereoset"], "metrics": ["accuracy"], "model-index": [{"name": "bert-large-uncased_stereoset_finetuned", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "stereoset", "type": "stereoset", "config": "intersentence", "split": "validation", "args": "intersentence"}, "metrics": [{"type": "accuracy", "value": 0.771585557299843, "name": "Accuracy"}]}]}]}
transformers pytorch bert text-classification generated_from_trainer dataset:stereoset license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #dataset-stereoset #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

bert-large-uncased\_stereoset\_finetuned
========================================


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


* Loss: 1.0729
* Accuracy: 0.7716


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: 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: 10


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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: 10 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #dataset-stereoset #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: 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: 10 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #dataset-stereoset #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: 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: 10### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1
* Datasets 2.9.0
* Tokenizers 0.13.2