---
license: apache-2.0
base_model: t5-large
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: t5-large_cola_dense_epochs-5
  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: 0.837967401725791
---

<!-- 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-large_cola_dense_epochs-5

This model is a fine-tuned version of [t5-large](https://huggingface.co/t5-large) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9474
- Accuracy: 0.8380

## 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: 32
- seed: 0
- 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: 20
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4193        | 0.37  | 50   | 0.6334          | 0.7996   |
| 0.3251        | 0.75  | 100  | 0.5550          | 0.8092   |
| 0.2903        | 1.12  | 150  | 0.5062          | 0.8255   |
| 0.2551        | 1.49  | 200  | 0.4837          | 0.8341   |
| 0.2893        | 1.87  | 250  | 0.4571          | 0.8360   |
| 0.175         | 2.24  | 300  | 1.0091          | 0.8351   |
| 0.17          | 2.61  | 350  | 0.6112          | 0.8418   |
| 0.1838        | 2.99  | 400  | 0.5199          | 0.8389   |
| 0.1342        | 3.36  | 450  | 1.7694          | 0.8408   |
| 0.1458        | 3.73  | 500  | 1.9474          | 0.8380   |
| 0.0828        | 4.1   | 550  | 1.6033          | 0.8428   |
| 0.096         | 4.48  | 600  | 1.9796          | 0.8418   |
| 0.2999        | 4.85  | 650  | 1.7943          | 0.8456   |


### Framework versions

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