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_mnli_192
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE MNLI
      type: glue
      config: mnli
      split: validation_matched
      args: mnli
    metrics:
    - type: accuracy
      value: 0.57740032546786
      name: Accuracy
---

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# distilbert_sa_GLUE_Experiment_logit_kd_mnli_192

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the GLUE MNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5326
- Accuracy: 0.5774

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.5885        | 1.0   | 1534  | 0.5621          | 0.5096   |
| 0.5572        | 2.0   | 3068  | 0.5481          | 0.5303   |
| 0.5456        | 3.0   | 4602  | 0.5473          | 0.5347   |
| 0.5373        | 4.0   | 6136  | 0.5404          | 0.5533   |
| 0.5299        | 5.0   | 7670  | 0.5371          | 0.5629   |
| 0.5235        | 6.0   | 9204  | 0.5361          | 0.5671   |
| 0.5172        | 7.0   | 10738 | 0.5360          | 0.5645   |
| 0.5114        | 8.0   | 12272 | 0.5391          | 0.5664   |
| 0.5058        | 9.0   | 13806 | 0.5332          | 0.5839   |
| 0.5004        | 10.0  | 15340 | 0.5294          | 0.5867   |
| 0.4951        | 11.0  | 16874 | 0.5284          | 0.5905   |
| 0.4901        | 12.0  | 18408 | 0.5309          | 0.5892   |
| 0.4853        | 13.0  | 19942 | 0.5334          | 0.5967   |
| 0.4804        | 14.0  | 21476 | 0.5344          | 0.5954   |
| 0.4754        | 15.0  | 23010 | 0.5297          | 0.5987   |
| 0.4707        | 16.0  | 24544 | 0.5348          | 0.5989   |


### Framework versions

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