---
license: apache-2.0
base_model: t5-large
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: t5-large_cola_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: 0.873046875
---

<!-- 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

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: 0.4531
- Accuracy: 0.8730

## 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
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6179        | 0.05  | 25   | 0.7262          | 0.6913   |
| 0.5561        | 0.11  | 50   | 0.5504          | 0.6961   |
| 0.5041        | 0.16  | 75   | 0.5027          | 0.7996   |
| 0.454         | 0.21  | 100  | 0.5353          | 0.7881   |
| 0.3981        | 0.27  | 125  | 0.5393          | 0.8063   |
| 0.4205        | 0.32  | 150  | 0.5582          | 0.7987   |
| 0.4305        | 0.37  | 175  | 0.4384          | 0.8073   |
| 0.4041        | 0.42  | 200  | 0.5255          | 0.8140   |
| 0.4319        | 0.48  | 225  | 0.5297          | 0.8102   |
| 0.3674        | 0.53  | 250  | 0.4788          | 0.8226   |
| 0.4013        | 0.58  | 275  | 0.5254          | 0.8150   |
| 0.4003        | 0.64  | 300  | 0.4980          | 0.8044   |
| 0.3794        | 0.69  | 325  | 0.4988          | 0.8188   |
| 0.4002        | 0.74  | 350  | 0.4188          | 0.8274   |
| 0.3793        | 0.8   | 375  | 0.4412          | 0.8188   |
| 0.3502        | 0.85  | 400  | 0.4862          | 0.8178   |
| 0.3563        | 0.9   | 425  | 0.4951          | 0.8082   |
| 0.3962        | 0.96  | 450  | 0.5133          | 0.8073   |
| 0.3474        | 1.01  | 475  | 0.4908          | 0.8265   |
| 0.22          | 1.06  | 500  | 0.6653          | 0.8198   |
| 0.2745        | 1.11  | 525  | 0.4787          | 0.8360   |
| 0.2181        | 1.17  | 550  | 0.6265          | 0.8245   |
| 0.283         | 1.22  | 575  | 0.6629          | 0.8265   |
| 0.311         | 1.27  | 600  | 0.4652          | 0.8399   |
| 0.2169        | 1.33  | 625  | 0.5805          | 0.8370   |
| 0.2764        | 1.38  | 650  | 0.5420          | 0.8322   |
| 0.2186        | 1.43  | 675  | 0.5668          | 0.8322   |
| 0.3297        | 1.49  | 700  | 0.6130          | 0.8332   |
| 0.2419        | 1.54  | 725  | 0.4862          | 0.8332   |
| 0.2713        | 1.59  | 750  | 0.4718          | 0.8255   |
| 0.2681        | 1.65  | 775  | 0.4710          | 0.8322   |
| 0.231         | 1.7   | 800  | 0.6525          | 0.8121   |
| 0.2286        | 1.75  | 825  | 0.5772          | 0.8236   |
| 0.2965        | 1.8   | 850  | 0.5093          | 0.8303   |
| 0.2791        | 1.86  | 875  | 0.5118          | 0.8303   |
| 0.276         | 1.91  | 900  | 0.5549          | 0.8313   |
| 0.2555        | 1.96  | 925  | 0.5499          | 0.8255   |
| 0.2361        | 2.02  | 950  | 0.6162          | 0.8245   |
| 0.1706        | 2.07  | 975  | 0.5747          | 0.8380   |
| 0.1566        | 2.12  | 1000 | 1.1363          | 0.8265   |
| 0.2285        | 2.18  | 1025 | 0.9228          | 0.8341   |
| 0.1501        | 2.23  | 1050 | 0.7669          | 0.8284   |
| 0.1484        | 2.28  | 1075 | 0.8961          | 0.8380   |
| 0.1639        | 2.34  | 1100 | 1.1919          | 0.8303   |
| 0.1021        | 2.39  | 1125 | 3.1020          | 0.8351   |
| 0.1543        | 2.44  | 1150 | 3.1121          | 0.8332   |
| 0.208         | 2.49  | 1175 | 0.8105          | 0.8265   |
| 0.1513        | 2.55  | 1200 | 0.6624          | 0.8360   |
| 0.1866        | 2.6   | 1225 | 0.5803          | 0.8255   |
| 0.1504        | 2.65  | 1250 | 0.7874          | 0.8341   |
| 0.1929        | 2.71  | 1275 | 0.6037          | 0.8293   |
| 0.1972        | 2.76  | 1300 | 0.8352          | 0.8217   |
| 0.1037        | 2.81  | 1325 | 1.9576          | 0.8293   |
| 0.1279        | 2.87  | 1350 | 3.1590          | 0.8303   |
| 0.2085        | 2.92  | 1375 | 4.3899          | 0.8284   |
| 0.191         | 2.97  | 1400 | 3.4493          | 0.8341   |
| 0.1469        | 3.03  | 1425 | 2.4196          | 0.8303   |
| 0.1009        | 3.08  | 1450 | 2.8744          | 0.8360   |
| 0.1243        | 3.13  | 1475 | 3.1569          | 0.8380   |
| 0.0695        | 3.18  | 1500 | 4.7343          | 0.8389   |
| 0.3294        | 3.24  | 1525 | 5.9461          | 0.8370   |
| 0.35          | 3.29  | 1550 | 6.4079          | 0.8341   |
| 0.1144        | 3.34  | 1575 | 5.5799          | 0.8313   |
| 0.1151        | 3.4   | 1600 | 5.1090          | 0.8332   |
| 0.1197        | 3.45  | 1625 | 5.1001          | 0.8341   |
| 0.6171        | 3.5   | 1650 | 4.7312          | 0.8360   |
| 0.1307        | 3.56  | 1675 | 4.3671          | 0.8360   |


### Framework versions

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