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---
language:
- en
base_model: google-t5/t5-base
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: SST2
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE SST2
type: glue
args: sst2
metrics:
- name: Accuracy
type: accuracy
value: 0.948394495412844
---
<!-- 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. -->
# SST2
This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on the GLUE SST2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2225
- Accuracy: 0.9484
## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1443 | 1.0 | 2105 | 0.2072 | 0.9323 |
| 0.1152 | 2.0 | 4210 | 0.2127 | 0.9404 |
| 0.0849 | 3.0 | 6315 | 0.2156 | 0.9438 |
| 0.0709 | 4.0 | 8420 | 0.2225 | 0.9484 |
| 0.06 | 5.0 | 10525 | 0.2719 | 0.9404 |
| 0.0507 | 6.0 | 12630 | 0.2911 | 0.9404 |
| 0.0435 | 7.0 | 14735 | 0.3279 | 0.9335 |
| 0.0357 | 8.0 | 16840 | 0.3566 | 0.9312 |
| 0.0274 | 9.0 | 18945 | 0.3876 | 0.9358 |
| 0.0253 | 10.0 | 21050 | 0.4034 | 0.9381 |
### Framework versions
- Transformers 4.43.3
- Pytorch 1.11.0+cu113
- Datasets 2.20.0
- Tokenizers 0.19.1
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