---
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: t5-base_cola_dense_epochs-6_exp_size_4
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: glue
      type: glue
      config: cola
      split: validation
      args: cola
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8235858101629914
---

<!-- 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-base_cola_dense_epochs-6_exp_size_4

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4622
- Accuracy: 0.8236

## 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: 64
- seed: 0
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5883        | 0.19  | 50   | 0.5895          | 0.6913   |
| 0.4961        | 0.37  | 100  | 0.5788          | 0.7574   |
| 0.5036        | 0.56  | 150  | 0.5192          | 0.7891   |
| 0.4038        | 0.75  | 200  | 0.4774          | 0.8025   |
| 0.4461        | 0.93  | 250  | 0.5380          | 0.7929   |
| 0.3573        | 1.12  | 300  | 0.5382          | 0.8169   |
| 0.3508        | 1.31  | 350  | 0.4526          | 0.8255   |
| 0.3379        | 1.49  | 400  | 0.4777          | 0.8245   |
| 0.3964        | 1.68  | 450  | 0.5148          | 0.8178   |
| 0.4137        | 1.87  | 500  | 0.4622          | 0.8236   |
| 0.3036        | 2.05  | 550  | 0.5171          | 0.8236   |
| 0.2913        | 2.24  | 600  | 0.5269          | 0.8322   |
| 0.277         | 2.43  | 650  | 0.5298          | 0.8293   |
| 0.2431        | 2.61  | 700  | 0.5129          | 0.8313   |
| 0.3551        | 2.8   | 750  | 0.5396          | 0.8255   |
| 0.2697        | 2.99  | 800  | 0.5307          | 0.8293   |
| 0.2494        | 3.17  | 850  | 0.5549          | 0.8332   |
| 0.2734        | 3.36  | 900  | 0.5431          | 0.8255   |
| 0.2886        | 3.54  | 950  | 0.5412          | 0.8245   |
| 0.3155        | 3.73  | 1000 | 0.5409          | 0.8284   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.0.1+cu117
- Datasets 2.9.0
- Tokenizers 0.14.1