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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- crows_pairs
metrics:
- accuracy
model-index:
- name: t5-small_crows_pairs_finetuned_HBRPOI
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: crows_pairs
type: crows_pairs
config: crows_pairs
split: test
args: crows_pairs
metrics:
- name: Accuracy
type: accuracy
value: 0.6490066225165563
---
<!-- 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_crows_pairs_finetuned_HBRPOI
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the crows_pairs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3485
- Accuracy: 0.6490
- Tp: 0.4934
- Tn: 0.1556
- Fp: 0.3411
- Fn: 0.0099
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|
| 0.4336 | 1.05 | 20 | 0.3559 | 0.5033 | 0.5033 | 0.0 | 0.4967 | 0.0 |
| 0.3726 | 2.11 | 40 | 0.3608 | 0.5033 | 0.5033 | 0.0 | 0.4967 | 0.0 |
| 0.317 | 3.16 | 60 | 0.3112 | 0.5099 | 0.5033 | 0.0066 | 0.4901 | 0.0 |
| 0.259 | 4.21 | 80 | 0.2822 | 0.5662 | 0.5 | 0.0662 | 0.4305 | 0.0033 |
| 0.2439 | 5.26 | 100 | 0.3249 | 0.7119 | 0.4934 | 0.2185 | 0.2781 | 0.0099 |
| 0.1824 | 6.32 | 120 | 0.3082 | 0.6093 | 0.4934 | 0.1159 | 0.3808 | 0.0099 |
| 0.1549 | 7.37 | 140 | 0.3217 | 0.5960 | 0.4967 | 0.0993 | 0.3974 | 0.0066 |
| 0.1312 | 8.42 | 160 | 0.3365 | 0.6325 | 0.4934 | 0.1391 | 0.3576 | 0.0099 |
| 0.1158 | 9.47 | 180 | 0.3485 | 0.6490 | 0.4934 | 0.1556 | 0.3411 | 0.0099 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2
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