---
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