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---
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: t5-base_cola_dense
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: 0.6912751677852349
---
<!-- 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-base_cola_dense
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: 0.6351
- Accuracy: 0.6913
## 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: 42
- 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: 200
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6331 | 0.07 | 10 | 0.6263 | 0.6855 |
| 0.626 | 0.15 | 20 | 0.6247 | 0.6826 |
| 0.6412 | 0.22 | 30 | 0.6240 | 0.6865 |
| 0.6497 | 0.3 | 40 | 0.6210 | 0.6874 |
| 0.6226 | 0.37 | 50 | 0.6213 | 0.6874 |
| 0.6183 | 0.45 | 60 | 0.6198 | 0.6894 |
| 0.6034 | 0.52 | 70 | 0.6202 | 0.6894 |
| 0.5802 | 0.6 | 80 | 0.6219 | 0.6913 |
| 0.6005 | 0.67 | 90 | 0.6261 | 0.6913 |
| 0.6178 | 0.75 | 100 | 0.6331 | 0.6922 |
| 0.5887 | 0.82 | 110 | 0.6344 | 0.6913 |
| 0.6492 | 0.9 | 120 | 0.6371 | 0.6913 |
| 0.6333 | 0.97 | 130 | 0.6376 | 0.6913 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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