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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- stereoset
metrics:
- accuracy
model-index:
- name: t5-small_stereoset_finetuned_HBRPOI
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: stereoset
type: stereoset
config: intersentence
split: validation
args: intersentence
metrics:
- name: Accuracy
type: accuracy
value: 0.6028257456828885
---
<!-- 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_stereoset_finetuned_HBRPOI
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the stereoset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4383
- Accuracy: 0.6028
- Tp: 0.4890
- Tn: 0.1138
- Fp: 0.3854
- Fn: 0.0118
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|
| 0.4447 | 0.43 | 20 | 0.3978 | 0.5008 | 0.5008 | 0.0 | 0.4992 | 0.0 |
| 0.3776 | 0.85 | 40 | 0.3448 | 0.6232 | 0.5008 | 0.1224 | 0.3768 | 0.0 |
| 0.3649 | 1.28 | 60 | 0.3269 | 0.5612 | 0.5 | 0.0612 | 0.4380 | 0.0008 |
| 0.3275 | 1.7 | 80 | 0.3218 | 0.5330 | 0.4992 | 0.0338 | 0.4655 | 0.0016 |
| 0.2969 | 2.13 | 100 | 0.3104 | 0.6256 | 0.4961 | 0.1295 | 0.3697 | 0.0047 |
| 0.3283 | 2.55 | 120 | 0.3111 | 0.5730 | 0.4992 | 0.0738 | 0.4254 | 0.0016 |
| 0.3046 | 2.98 | 140 | 0.3040 | 0.5416 | 0.4992 | 0.0424 | 0.4568 | 0.0016 |
| 0.2603 | 3.4 | 160 | 0.3057 | 0.5447 | 0.4992 | 0.0455 | 0.4537 | 0.0016 |
| 0.2828 | 3.83 | 180 | 0.3186 | 0.5479 | 0.4984 | 0.0495 | 0.4498 | 0.0024 |
| 0.2326 | 4.26 | 200 | 0.3036 | 0.6193 | 0.4937 | 0.1256 | 0.3736 | 0.0071 |
| 0.2289 | 4.68 | 220 | 0.3328 | 0.5479 | 0.4976 | 0.0502 | 0.4490 | 0.0031 |
| 0.2234 | 5.11 | 240 | 0.3140 | 0.5777 | 0.4976 | 0.0801 | 0.4192 | 0.0031 |
| 0.2225 | 5.53 | 260 | 0.3245 | 0.5691 | 0.4976 | 0.0714 | 0.4278 | 0.0031 |
| 0.187 | 5.96 | 280 | 0.3300 | 0.5785 | 0.4961 | 0.0824 | 0.4168 | 0.0047 |
| 0.179 | 6.38 | 300 | 0.3344 | 0.5848 | 0.4961 | 0.0887 | 0.4105 | 0.0047 |
| 0.1523 | 6.81 | 320 | 0.3528 | 0.5895 | 0.4969 | 0.0926 | 0.4066 | 0.0039 |
| 0.1499 | 7.23 | 340 | 0.3788 | 0.6232 | 0.4906 | 0.1327 | 0.3666 | 0.0102 |
| 0.1292 | 7.66 | 360 | 0.3889 | 0.5942 | 0.4914 | 0.1028 | 0.3964 | 0.0094 |
| 0.13 | 8.09 | 380 | 0.3959 | 0.5903 | 0.4937 | 0.0965 | 0.4027 | 0.0071 |
| 0.1216 | 8.51 | 400 | 0.4169 | 0.5856 | 0.4922 | 0.0934 | 0.4058 | 0.0086 |
| 0.1306 | 8.94 | 420 | 0.4227 | 0.6005 | 0.4898 | 0.1107 | 0.3885 | 0.0110 |
| 0.0968 | 9.36 | 440 | 0.4334 | 0.5965 | 0.4914 | 0.1052 | 0.3940 | 0.0094 |
| 0.1044 | 9.79 | 460 | 0.4383 | 0.6028 | 0.4890 | 0.1138 | 0.3854 | 0.0118 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2
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