transformers pytorch t5 text-classification generated_from_trainer dataset:glue base_model:google-t5/t5-base base_model:finetune:google-t5/t5-base license:apache-2.0 model-index autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: t5-base
datasets:
- glue
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: t5-base_cola_dense_epochs-3
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: glue
      type: glue
      config: cola
      split: validation
      args: cola
    metrics:
    - type: accuracy
      value: 0.8283796740172579
      name: Accuracy
---

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# t5-base_cola_dense_epochs-3

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: 0.5042
- Accuracy: 0.8284

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5796        | 0.19  | 50   | 0.5780          | 0.6913   |
| 0.4821        | 0.37  | 100  | 0.6683          | 0.7546   |
| 0.4703        | 0.56  | 150  | 0.4976          | 0.8035   |
| 0.4252        | 0.75  | 200  | 0.4958          | 0.8150   |
| 0.4915        | 0.93  | 250  | 0.5360          | 0.8044   |
| 0.3812        | 1.12  | 300  | 0.4645          | 0.8322   |
| 0.3603        | 1.31  | 350  | 0.4788          | 0.8293   |
| 0.3336        | 1.49  | 400  | 0.5135          | 0.8245   |
| 0.4157        | 1.68  | 450  | 0.5311          | 0.8322   |
| 0.4094        | 1.87  | 500  | 0.5042          | 0.8284   |
| 0.2836        | 2.05  | 550  | 0.5277          | 0.8313   |
| 0.2993        | 2.24  | 600  | 0.5515          | 0.8341   |
| 0.2843        | 2.43  | 650  | 0.5195          | 0.8332   |
| 0.2288        | 2.61  | 700  | 0.5129          | 0.8332   |
| 0.3165        | 2.8   | 750  | 0.5126          | 0.8360   |
| 0.2717        | 2.99  | 800  | 0.5083          | 0.8332   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
