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---
license: apache-2.0
base_model: t5-large
tags:
- generated_from_trainer
datasets:
- super_glue
metrics:
- accuracy
model-index:
- name: t5-large_boolq_dense_epochs-5
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: super_glue
type: super_glue
config: boolq
split: validation
args: boolq
metrics:
- name: Accuracy
type: accuracy
value: 0.846177370030581
---
<!-- 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_boolq_dense_epochs-5
This model is a fine-tuned version of [t5-large](https://huggingface.co/t5-large) on the super_glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3715
- Accuracy: 0.8462
## 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: 8
- eval_batch_size: 16
- seed: 0
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6792 | 0.17 | 50 | 0.6652 | 0.6217 |
| 0.66 | 0.34 | 100 | 0.6595 | 0.6220 |
| 0.6614 | 0.51 | 150 | 0.6548 | 0.6232 |
| 0.636 | 0.68 | 200 | 0.6122 | 0.6985 |
| 0.4882 | 0.85 | 250 | 0.4702 | 0.7847 |
| 0.5068 | 1.02 | 300 | 0.4639 | 0.7862 |
| 0.3332 | 1.19 | 350 | 0.5297 | 0.7908 |
| 0.4296 | 1.36 | 400 | 0.3955 | 0.8373 |
| 0.356 | 1.53 | 450 | 0.4013 | 0.8410 |
| 0.3227 | 1.7 | 500 | 0.3715 | 0.8462 |
| 0.3516 | 1.87 | 550 | 0.3724 | 0.8428 |
| 0.2169 | 2.04 | 600 | 0.3906 | 0.8477 |
| 0.2199 | 2.21 | 650 | 0.4061 | 0.8572 |
| 0.1969 | 2.37 | 700 | 0.4351 | 0.8550 |
| 0.2713 | 2.54 | 750 | 0.5411 | 0.8584 |
| 0.2458 | 2.71 | 800 | 0.3924 | 0.8627 |
| 0.2134 | 2.88 | 850 | 0.3973 | 0.8630 |
| 0.1636 | 3.05 | 900 | 0.4933 | 0.8590 |
| 0.1108 | 3.22 | 950 | 0.9926 | 0.8621 |
| 0.1433 | 3.39 | 1000 | 0.6679 | 0.8602 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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