---
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: t5-base_cola_dense_sp0_ar0
  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: 0.0
---

<!-- 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_sp0_ar0

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: 4.9143
- Accuracy: 0.0

## 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: 1
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5646        | 0.09  | 25   | 0.6556          | 0.6913   |
| 0.6392        | 0.19  | 50   | 0.5933          | 0.6913   |
| 0.5668        | 0.28  | 75   | 0.5673          | 0.6913   |
| 0.4777        | 0.37  | 100  | 0.5130          | 0.7872   |
| 0.4982        | 0.47  | 125  | 0.5462          | 0.7987   |
| 0.515         | 0.56  | 150  | 0.4918          | 0.8025   |
| 0.5279        | 0.65  | 175  | 0.4923          | 0.7900   |
| 0.4246        | 0.75  | 200  | 0.5310          | 0.7958   |
| 0.4437        | 0.84  | 225  | 0.4455          | 0.8159   |
| 0.4251        | 0.93  | 250  | 0.4847          | 0.8111   |
| 0.2875        | 1.03  | 275  | 0.5152          | 0.8102   |
| 0.3736        | 1.12  | 300  | 0.5038          | 0.8130   |
| 0.3489        | 1.21  | 325  | 0.4612          | 0.8159   |
| 0.3729        | 1.31  | 350  | 0.5098          | 0.8102   |
| 0.3574        | 1.4   | 375  | 0.5389          | 0.8121   |
| 0.3897        | 1.49  | 400  | 0.4788          | 0.8130   |
| 0.3785        | 1.59  | 425  | 0.4827          | 0.8150   |
| 0.4429        | 1.68  | 450  | 0.5501          | 0.8063   |
| 0.3893        | 1.77  | 475  | 0.4393          | 0.8245   |
| 0.3531        | 1.87  | 500  | 0.4769          | 0.8255   |
| 0.3853        | 1.96  | 525  | 0.4711          | 0.8284   |
| 0.3173        | 2.05  | 550  | 0.5262          | 0.8226   |
| 0.3102        | 2.15  | 575  | 0.5084          | 0.8284   |
| 0.3236        | 2.24  | 600  | 0.5517          | 0.8293   |
| 0.2618        | 2.33  | 625  | 0.5825          | 0.8322   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.11.6