transformers pytorch t5 text-classification generated_from_trainer dataset:glue base_model:lukeleeai/t5-base_cola_densedense_baseline base_model:finetune:lukeleeai/t5-base_cola_densedense_baseline license:apache-2.0 model-index autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: lukeleeai/t5-base_cola_densedense_baseline
datasets:
- glue
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: t5-base_cola_dense_mare_mlp_einsum
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: glue
      type: glue
      config: cola
      split: validation
      args: cola
    metrics:
    - type: accuracy
      value: 0.7516778523489933
      name: Accuracy
---

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# t5-base_cola_dense_mare_mlp_einsum

This model is a fine-tuned version of [lukeleeai/t5-base_cola_densedense_baseline](https://huggingface.co/lukeleeai/t5-base_cola_densedense_baseline) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7682
- Accuracy: 0.7517

## 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: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5856        | 0.19  | 50   | 0.6260          | 0.6913   |
| 0.5836        | 0.37  | 100  | 0.6029          | 0.6913   |
| 0.5724        | 0.56  | 150  | 0.6055          | 0.6932   |
| 0.6635        | 0.75  | 200  | 0.6171          | 0.6922   |
| 0.5634        | 0.93  | 250  | 0.6162          | 0.6999   |
| 0.5361        | 1.12  | 300  | 0.6142          | 0.6932   |
| 0.5426        | 1.31  | 350  | 0.5920          | 0.7057   |
| 0.6255        | 1.5   | 400  | 0.5884          | 0.7095   |
| 0.6312        | 1.68  | 450  | 0.5723          | 0.7095   |
| 0.5686        | 1.87  | 500  | 0.5894          | 0.7057   |
| 0.5486        | 2.06  | 550  | 0.5590          | 0.7124   |
| 0.4436        | 2.24  | 600  | 0.5838          | 0.7220   |
| 0.4405        | 2.43  | 650  | 0.6176          | 0.7315   |
| 0.4785        | 2.62  | 700  | 0.6236          | 0.7296   |
| 0.5759        | 2.8   | 750  | 0.6233          | 0.7191   |
| 0.6156        | 2.99  | 800  | 0.6807          | 0.7392   |
| 0.4843        | 3.18  | 850  | 0.6337          | 0.7373   |
| 0.5408        | 3.36  | 900  | 0.7107          | 0.7392   |
| 0.4327        | 3.55  | 950  | 0.6256          | 0.7239   |
| 0.4318        | 3.74  | 1000 | 0.6951          | 0.7478   |
| 0.4047        | 3.93  | 1050 | 0.6566          | 0.7430   |
| 0.423         | 4.11  | 1100 | 0.6731          | 0.7440   |
| 0.3919        | 4.3   | 1150 | 0.6750          | 0.7392   |
| 0.4041        | 4.49  | 1200 | 0.6464          | 0.7421   |
| 0.3941        | 4.67  | 1250 | 0.6580          | 0.7517   |
| 0.3834        | 4.86  | 1300 | 0.6257          | 0.7459   |
| 0.2678        | 5.05  | 1350 | 0.6464          | 0.7555   |
| 0.3202        | 5.23  | 1400 | 0.7048          | 0.7507   |
| 0.2869        | 5.42  | 1450 | 0.7405          | 0.7565   |
| 0.3359        | 5.61  | 1500 | 0.6393          | 0.7593   |
| 0.3528        | 5.79  | 1550 | 0.6249          | 0.7555   |
| 0.3304        | 5.98  | 1600 | 0.6349          | 0.7565   |
| 0.2862        | 6.17  | 1650 | 0.7497          | 0.7670   |
| 0.2315        | 6.36  | 1700 | 0.7787          | 0.7622   |
| 0.3251        | 6.54  | 1750 | 0.7038          | 0.7555   |
| 0.3584        | 6.73  | 1800 | 0.7732          | 0.7603   |
| 0.1804        | 6.92  | 1850 | 0.8226          | 0.7584   |
| 0.2264        | 7.1   | 1900 | 0.7420          | 0.7613   |
| 0.2374        | 7.29  | 1950 | 0.7825          | 0.7507   |
| 0.203         | 7.48  | 2000 | 0.7575          | 0.7641   |
| 0.238         | 7.66  | 2050 | 1.9945          | 0.7603   |
| 0.2328        | 7.85  | 2100 | 0.7682          | 0.7517   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.9.0
- Tokenizers 0.11.6
