---
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: t5-base_rte_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_rte_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: 0.9086
- 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: 8
- eval_batch_size: 16
- seed: 1
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6787        | 0.16  | 25   | 0.6850          | 0.5307   |
| 0.7034        | 0.32  | 50   | 0.6689          | 0.5704   |
| 0.6478        | 0.48  | 75   | 0.6356          | 0.6570   |
| 0.6889        | 0.64  | 100  | 0.6188          | 0.6859   |
| 0.588         | 0.8   | 125  | 0.5892          | 0.6859   |
| 0.5989        | 0.96  | 150  | 0.6802          | 0.6606   |
| 0.5392        | 1.12  | 175  | 0.5836          | 0.7329   |
| 0.5497        | 1.28  | 200  | 0.6758          | 0.6715   |
| 0.5567        | 1.44  | 225  | 0.7056          | 0.6643   |
| 0.5063        | 1.6   | 250  | 0.5617          | 0.7401   |
| 0.5644        | 1.76  | 275  | 0.5737          | 0.7256   |
| 0.6018        | 1.92  | 300  | 0.6179          | 0.7112   |
| 0.4554        | 2.08  | 325  | 0.5339          | 0.7509   |
| 0.3778        | 2.24  | 350  | 0.5495          | 0.7726   |


### Framework versions

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