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_wnli_384
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE WNLI
      type: glue
      config: wnli
      split: validation
      args: wnli
    metrics:
    - type: accuracy
      value: 0.5633802816901409
      name: Accuracy
---

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# distilbert_sa_GLUE_Experiment_wnli_384

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the GLUE WNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6861
- Accuracy: 0.5634

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7012        | 1.0   | 3    | 0.7047          | 0.4366   |
| 0.7043        | 2.0   | 6    | 0.6952          | 0.4366   |
| 0.6928        | 3.0   | 9    | 0.6861          | 0.5634   |
| 0.6998        | 4.0   | 12   | 0.6874          | 0.5634   |
| 0.6927        | 5.0   | 15   | 0.6957          | 0.4366   |
| 0.6952        | 6.0   | 18   | 0.7001          | 0.4366   |
| 0.6966        | 7.0   | 21   | 0.6927          | 0.5634   |
| 0.6917        | 8.0   | 24   | 0.6909          | 0.5634   |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.8.0
- Tokenizers 0.13.2
