transformers pytorch t5 text-classification generated_from_trainer dataset:glue base_model:google-t5/t5-large base_model:finetune:google-t5/t5-large license:apache-2.0 model-index autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: t5-large
datasets:
- glue
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: t5-large_cola_moe_ex12_epochs-1_mare_mlp
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: glue
      type: glue
      config: cola
      split: train[:64]
      args: cola
    metrics:
    - type: accuracy
      value: 0.46153846153846156
      name: Accuracy
---

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# t5-large_cola_moe_ex12_epochs-1_mare_mlp

This model is a fine-tuned version of [t5-large](https://huggingface.co/t5-large) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7266
- Accuracy: 0.4615

## 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: 1
- distributed_type: multi-GPU
- 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: 1

### Training results



### Framework versions

- Transformers 4.34.1
- Pytorch 2.0.1+cu117
- Datasets 2.9.0
- Tokenizers 0.14.1
