---
license: apache-2.0
base_model: t5-large
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: t5-large_cola_sp0_ar0_one
  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: 0.87890625
---

<!-- 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_sp0_ar0_one

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: 0.4212
- Accuracy: 0.8789

## 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: 16
- eval_batch_size: 32
- seed: 1
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- training_steps: 0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6975        | 0.05  | 25   | 0.6708          | 0.6913   |
| 0.5747        | 0.11  | 50   | 0.5123          | 0.7210   |
| 0.4924        | 0.16  | 75   | 0.5004          | 0.7939   |
| 0.4259        | 0.21  | 100  | 0.4760          | 0.7987   |
| 0.3834        | 0.27  | 125  | 0.5001          | 0.8111   |
| 0.3942        | 0.32  | 150  | 0.4982          | 0.8092   |
| 0.4213        | 0.37  | 175  | 0.5078          | 0.8150   |
| 0.3845        | 0.42  | 200  | 0.4346          | 0.8092   |
| 0.4145        | 0.48  | 225  | 0.4562          | 0.8150   |
| 0.3751        | 0.53  | 250  | 0.4948          | 0.8169   |
| 0.4134        | 0.58  | 275  | 0.4356          | 0.8236   |
| 0.3777        | 0.64  | 300  | 0.4627          | 0.8188   |
| 0.3815        | 0.69  | 325  | 0.4772          | 0.8226   |
| 0.367         | 0.74  | 350  | 0.4117          | 0.8313   |
| 0.342         | 0.8   | 375  | 0.4177          | 0.8351   |
| 0.3136        | 0.85  | 400  | 0.5026          | 0.8265   |
| 0.3222        | 0.9   | 425  | 0.5323          | 0.8303   |
| 0.3863        | 0.96  | 450  | 0.4937          | 0.8245   |
| 0.348         | 1.01  | 475  | 0.4704          | 0.8188   |
| 0.2134        | 1.06  | 500  | 0.6430          | 0.8207   |
| 0.2671        | 1.11  | 525  | 0.5518          | 0.8226   |
| 0.1892        | 1.17  | 550  | 0.5869          | 0.8370   |
| 0.2184        | 1.22  | 575  | 0.5816          | 0.8332   |
| 0.22          | 1.27  | 600  | 0.5451          | 0.8274   |
| 0.1982        | 1.33  | 625  | 0.7300          | 0.8313   |
| 0.2734        | 1.38  | 650  | 0.7040          | 0.8351   |
| 0.2186        | 1.43  | 675  | 0.6650          | 0.8341   |
| 0.2835        | 1.49  | 700  | 0.6628          | 0.8322   |
| 0.2503        | 1.54  | 725  | 0.5194          | 0.8341   |
| 0.2438        | 1.59  | 750  | 0.5362          | 0.8313   |
| 0.2307        | 1.65  | 775  | 0.5405          | 0.8293   |
| 0.2111        | 1.7   | 800  | 0.6129          | 0.8265   |
| 0.1952        | 1.75  | 825  | 0.6411          | 0.8255   |
| 0.2873        | 1.8   | 850  | 0.6279          | 0.8245   |
| 0.295         | 1.86  | 875  | 0.5938          | 0.8236   |
| 0.2967        | 1.91  | 900  | 0.5694          | 0.8265   |
| 0.2128        | 1.96  | 925  | 0.5576          | 0.8265   |


### Framework versions

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