transformers pytorch tensorboard distilbert text-classification generated_from_trainer en dataset:glue license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- glue
language:
- en
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: distilbert_sa_GLUE_Experiment_logit_kd_data_aug_rte_192
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE RTE
      type: glue
      args: rte
    metrics:
    - type: accuracy
      value: 0.51985559566787
      name: Accuracy
---

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# distilbert_sa_GLUE_Experiment_logit_kd_data_aug_rte_192

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the GLUE RTE dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5485
- Accuracy: 0.5199

## 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: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.348         | 1.0   | 568  | 0.5499          | 0.4874   |
| 0.2888        | 2.0   | 1136 | 0.5640          | 0.4982   |
| 0.2849        | 3.0   | 1704 | 0.5618          | 0.5199   |
| 0.2833        | 4.0   | 2272 | 0.5618          | 0.5018   |
| 0.2823        | 5.0   | 2840 | 0.5610          | 0.5090   |
| 0.2816        | 6.0   | 3408 | 0.5485          | 0.5199   |
| 0.281         | 7.0   | 3976 | 0.5527          | 0.5126   |
| 0.2805        | 8.0   | 4544 | 0.5578          | 0.5054   |
| 0.2798        | 9.0   | 5112 | 0.5575          | 0.5343   |
| 0.2796        | 10.0  | 5680 | 0.5533          | 0.5199   |
| 0.2793        | 11.0  | 6248 | 0.5534          | 0.5090   |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.9.0
- Tokenizers 0.13.2
