transformers pytorch t5 text-classification generated_from_trainer dataset:glue base_model:google-t5/t5-base base_model:finetune:google-t5/t5-base license:apache-2.0 model-index autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: t5-base
datasets:
- glue
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: t5-base_cola_moe_ex16_epochs-5_collected-stats
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: glue
      type: glue
      config: cola
      split: validation
      args: cola
    metrics:
    - type: accuracy
      value: 0.8302972195589645
      name: Accuracy
---

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# t5-base_cola_moe_ex16_epochs-5_collected-stats

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: 0.5254
- Accuracy: 0.8303

## 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: 20
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5766        | 0.37  | 50   | 0.5459          | 0.7009   |
| 0.4641        | 0.75  | 100  | 0.4948          | 0.7996   |
| 0.3657        | 1.12  | 150  | 0.5502          | 0.8111   |
| 0.4043        | 1.49  | 200  | 0.4791          | 0.8198   |
| 0.3875        | 1.87  | 250  | 0.4936          | 0.8217   |
| 0.3507        | 2.24  | 300  | 0.4735          | 0.8217   |
| 0.3255        | 2.61  | 350  | 0.5022          | 0.8198   |
| 0.3407        | 2.99  | 400  | 0.5193          | 0.8265   |
| 0.2576        | 3.36  | 450  | 0.5292          | 0.8303   |
| 0.3138        | 3.73  | 500  | 0.5254          | 0.8303   |
| 0.2866        | 4.1   | 550  | 0.5132          | 0.8313   |
| 0.284         | 4.48  | 600  | 0.5314          | 0.8274   |
| 0.3607        | 4.85  | 650  | 0.5357          | 0.8293   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
