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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: t5-small_winobias_finetuned_HBRPOI
results: []
---
<!-- 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. -->
# 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
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