---
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: train
      args: cola
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8813559322033898
---

<!-- 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: 0.4167
- Accuracy: 0.8814

## 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: 64
- eval_batch_size: 64
- seed: 0
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6749        | 0.19  | 10   | 0.6270          | 0.7095   |
| 0.5772        | 0.37  | 20   | 0.5947          | 0.7101   |
| 0.6066        | 0.56  | 30   | 0.5545          | 0.7101   |
| 0.5355        | 0.75  | 40   | 0.4788          | 0.7475   |
| 0.4398        | 0.93  | 50   | 0.3992          | 0.8469   |
| 0.3932        | 1.12  | 60   | 0.3737          | 0.8638   |
| 0.3756        | 1.31  | 70   | 0.3606          | 0.8650   |
| 0.4004        | 1.5   | 80   | 0.3645          | 0.8603   |
| 0.3198        | 1.68  | 90   | 0.3201          | 0.8749   |
| 0.3129        | 1.87  | 100  | 0.3638          | 0.8697   |
| 0.2763        | 2.06  | 110  | 0.3091          | 0.8819   |
| 0.3207        | 2.24  | 120  | 0.3781          | 0.8673   |
| 0.2614        | 2.43  | 130  | 0.3351          | 0.8773   |
| 0.2909        | 2.62  | 140  | 0.3404          | 0.8662   |
| 0.2899        | 2.8   | 150  | 0.3277          | 0.8796   |
| 0.2687        | 2.99  | 160  | 0.3520          | 0.8679   |
| 0.1993        | 3.18  | 170  | 0.3319          | 0.8854   |
| 0.2584        | 3.36  | 180  | 0.3901          | 0.8732   |
| 0.2502        | 3.55  | 190  | 0.3766          | 0.8773   |
| 0.2234        | 3.74  | 200  | 0.3360          | 0.8895   |
| 0.2101        | 3.93  | 210  | 0.3334          | 0.8849   |
| 0.1708        | 4.11  | 220  | 0.3819          | 0.8714   |
| 0.1664        | 4.3   | 230  | 0.3690          | 0.8773   |
| 0.2217        | 4.49  | 240  | 0.4181          | 0.8814   |
| 0.2034        | 4.67  | 250  | 0.3607          | 0.8796   |
| 0.1948        | 4.86  | 260  | 0.4167          | 0.8814   |


### Framework versions

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