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# t5-small_winobias_finetuned_HBRPOI

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3333
- 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: 0.0005
- 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Tp  | Tn     | Fp     | Fn  |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|:------:|:------:|:---:|
| 0.437         | 0.8   | 20   | 0.3545          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3996        | 1.6   | 40   | 0.3565          | 0.5025   | 0.5 | 0.0025 | 0.4975 | 0.0 |
| 0.3844        | 2.4   | 60   | 0.3498          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3728        | 3.2   | 80   | 0.3529          | 0.5013   | 0.5 | 0.0013 | 0.4987 | 0.0 |
| 0.3732        | 4.0   | 100  | 0.3482          | 0.5006   | 0.5 | 0.0006 | 0.4994 | 0.0 |
| 0.3798        | 4.8   | 120  | 0.3484          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3607        | 5.6   | 140  | 0.3475          | 0.5006   | 0.5 | 0.0006 | 0.4994 | 0.0 |
| 0.3688        | 6.4   | 160  | 0.3456          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3597        | 7.2   | 180  | 0.3445          | 0.5006   | 0.5 | 0.0006 | 0.4994 | 0.0 |
| 0.3658        | 8.0   | 200  | 0.3402          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3629        | 8.8   | 220  | 0.3362          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3393        | 9.6   | 240  | 0.3333          | 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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "t5-small_winobias_finetuned_HBRPOI", "results": []}]}
transformers pytorch t5 text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

t5-small\_winobias\_finetuned\_HBRPOI
=====================================


This model is a fine-tuned version of t5-small on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3333
* 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: 0.0005
* 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: 10


### 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: 0.0005
* 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: 10 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0005
* 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: 10 ### Training results ### Framework versions


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