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# t5-small_winobias_finetuned

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: 0.2473
- Accuracy: 0.5278
- Tp: 0.5
- Tn: 0.0278
- Fp: 0.4722
- 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: 0.0003
- 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 | Tp  | Tn     | Fp     | Fn  |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|:------:|:------:|:---:|
| 0.6334        | 0.8   | 20   | 0.3622          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.4058        | 1.6   | 40   | 0.3510          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3923        | 2.4   | 60   | 0.3511          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.376         | 3.2   | 80   | 0.3509          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3749        | 4.0   | 100  | 0.3502          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3895        | 4.8   | 120  | 0.3505          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3624        | 5.6   | 140  | 0.3508          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3754        | 6.4   | 160  | 0.3501          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3702        | 7.2   | 180  | 0.3576          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3748        | 8.0   | 200  | 0.3499          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3715        | 8.8   | 220  | 0.3482          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3576        | 9.6   | 240  | 0.3489          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3659        | 10.4  | 260  | 0.3510          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3565        | 11.2  | 280  | 0.3464          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.353         | 12.0  | 300  | 0.3474          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3614        | 12.8  | 320  | 0.3450          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3625        | 13.6  | 340  | 0.3458          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.36          | 14.4  | 360  | 0.3494          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3585        | 15.2  | 380  | 0.3435          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3541        | 16.0  | 400  | 0.3431          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3564        | 16.8  | 420  | 0.3414          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3462        | 17.6  | 440  | 0.3413          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3541        | 18.4  | 460  | 0.3382          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3579        | 19.2  | 480  | 0.3399          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3466        | 20.0  | 500  | 0.3317          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3314        | 20.8  | 520  | 0.3303          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.33          | 21.6  | 540  | 0.3246          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3279        | 22.4  | 560  | 0.3154          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3234        | 23.2  | 580  | 0.3050          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3193        | 24.0  | 600  | 0.2947          | 0.5      | 0.5 | 0.0    | 0.5    | 0.0 |
| 0.3086        | 24.8  | 620  | 0.2849          | 0.5013   | 0.5 | 0.0013 | 0.4987 | 0.0 |
| 0.2912        | 25.6  | 640  | 0.2748          | 0.5013   | 0.5 | 0.0013 | 0.4987 | 0.0 |
| 0.2787        | 26.4  | 660  | 0.2655          | 0.5107   | 0.5 | 0.0107 | 0.4893 | 0.0 |
| 0.2779        | 27.2  | 680  | 0.2581          | 0.5177   | 0.5 | 0.0177 | 0.4823 | 0.0 |
| 0.2697        | 28.0  | 700  | 0.2527          | 0.5170   | 0.5 | 0.0170 | 0.4830 | 0.0 |
| 0.2669        | 28.8  | 720  | 0.2495          | 0.5259   | 0.5 | 0.0259 | 0.4741 | 0.0 |
| 0.2654        | 29.6  | 740  | 0.2473          | 0.5278   | 0.5 | 0.0278 | 0.4722 | 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", "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
=============================


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


* Loss: 0.2473
* Accuracy: 0.5278
* Tp: 0.5
* Tn: 0.0278
* Fp: 0.4722
* 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: 0.0003
* 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: 0.0003
* 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 #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: 0.0003
* 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