---
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: t5-base_mrpc_dense_sp0_ar0
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: glue
      type: glue
      config: rte
      split: validation
      args: rte
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.0
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# t5-base_mrpc_dense_sp0_ar0

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: 1.0325
- Accuracy: 0.0

## 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
- 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.717         | 0.64  | 25   | 0.6894          | 0.5307   |
| 0.6467        | 1.28  | 50   | 0.6510          | 0.6173   |
| 0.6062        | 1.92  | 75   | 0.5660          | 0.7292   |
| 0.503         | 2.56  | 100  | 0.5416          | 0.7473   |
| 0.4691        | 3.21  | 125  | 0.5493          | 0.7220   |
| 0.4518        | 3.85  | 150  | 0.5516          | 0.7509   |
| 0.4087        | 4.49  | 175  | 0.5405          | 0.7690   |
| 0.3352        | 5.13  | 200  | 0.5216          | 0.7870   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.11.6