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_sst2_dense_epochs-5
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: glue
      type: glue
      config: sst2
      split: validation
      args: sst2
    metrics:
    - type: accuracy
      value: 0.9575688073394495
      name: Accuracy
---

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# t5-large_sst2_dense_epochs-5

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: 0.6867
- Accuracy: 0.9576

## 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: 256
- eval_batch_size: 256
- seed: 0
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 512
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2069        | 0.38  | 50   | 0.4171          | 0.9438   |
| 0.1627        | 0.76  | 100  | 0.3713          | 0.9518   |
| 0.1641        | 1.14  | 150  | 0.4802          | 0.9553   |
| 0.1261        | 1.52  | 200  | 0.2517          | 0.9541   |
| 0.128         | 1.89  | 250  | 0.2427          | 0.9633   |
| 0.0765        | 2.27  | 300  | 0.5854          | 0.9622   |
| 0.1547        | 2.65  | 350  | 0.6896          | 0.9507   |
| 0.0705        | 3.03  | 400  | 0.5790          | 0.9484   |
| 0.0683        | 3.41  | 450  | 0.3680          | 0.9564   |
| 0.0889        | 3.79  | 500  | 0.6867          | 0.9576   |
| 0.1541        | 4.17  | 550  | 0.6979          | 0.9576   |
| 0.0689        | 4.55  | 600  | 0.9328          | 0.9507   |
| 0.0964        | 4.92  | 650  | 0.6852          | 0.9587   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
