---
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