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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_moe_ex19_epochs-3_decoder_all_sparsity10_mare_mlp
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: 0.8322147651006712
---
<!-- 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_moe_ex19_epochs-3_decoder_all_sparsity10_mare_mlp
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: 0.6160
- Accuracy: 0.8322
## 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
- gradient_accumulation_steps: 2
- 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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5636 | 0.19 | 50 | 0.9030 | 0.8255 |
| 0.5623 | 0.37 | 100 | 0.7397 | 0.8322 |
| 0.571 | 0.56 | 150 | 0.7188 | 0.8159 |
| 0.4997 | 0.75 | 200 | 0.6449 | 0.8322 |
| 0.5069 | 0.93 | 250 | 0.5668 | 0.8332 |
| 0.374 | 1.12 | 300 | 0.6804 | 0.8245 |
| 0.3617 | 1.31 | 350 | 0.6122 | 0.8313 |
| 0.3928 | 1.5 | 400 | 0.5891 | 0.8274 |
| 0.3772 | 1.68 | 450 | 0.6124 | 0.8245 |
| 0.3275 | 1.87 | 500 | 0.5892 | 0.8255 |
| 0.2992 | 2.06 | 550 | 0.6055 | 0.8255 |
| 0.4092 | 2.24 | 600 | 0.6054 | 0.8293 |
| 0.288 | 2.43 | 650 | 0.5972 | 0.8313 |
| 0.3493 | 2.62 | 700 | 0.6449 | 0.8313 |
| 0.2419 | 2.8 | 750 | 0.6198 | 0.8332 |
| 0.3811 | 2.99 | 800 | 0.6252 | 0.8322 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu117
- Datasets 2.9.0
- Tokenizers 0.14.1
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