---
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: t5-base_cola_dense
  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: 0.6912751677852349
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# t5-base_cola_dense

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: 0.6351
- Accuracy: 0.6913

## 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: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6331        | 0.07  | 10   | 0.6263          | 0.6855   |
| 0.626         | 0.15  | 20   | 0.6247          | 0.6826   |
| 0.6412        | 0.22  | 30   | 0.6240          | 0.6865   |
| 0.6497        | 0.3   | 40   | 0.6210          | 0.6874   |
| 0.6226        | 0.37  | 50   | 0.6213          | 0.6874   |
| 0.6183        | 0.45  | 60   | 0.6198          | 0.6894   |
| 0.6034        | 0.52  | 70   | 0.6202          | 0.6894   |
| 0.5802        | 0.6   | 80   | 0.6219          | 0.6913   |
| 0.6005        | 0.67  | 90   | 0.6261          | 0.6913   |
| 0.6178        | 0.75  | 100  | 0.6331          | 0.6922   |
| 0.5887        | 0.82  | 110  | 0.6344          | 0.6913   |
| 0.6492        | 0.9   | 120  | 0.6371          | 0.6913   |
| 0.6333        | 0.97  | 130  | 0.6376          | 0.6913   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1