transformers pytorch tensorboard distilbert text-classification generated_from_trainer en dataset:glue model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- glue
language:
- en
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: distilbert_sa_GLUE_Experiment_logit_kd_pretrain_mrpc
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE MRPC
      type: glue
      config: mrpc
      split: validation
      args: mrpc
    metrics:
    - type: accuracy
      value: 0.5269607843137255
      name: Accuracy
    - type: f1
      value: 0.5089058524173028
      name: F1
---

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# distilbert_sa_GLUE_Experiment_logit_kd_pretrain_mrpc

This model is a fine-tuned version of [gokuls/distilbert_sa_pre-training-complete](https://huggingface.co/gokuls/distilbert_sa_pre-training-complete) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4973
- Accuracy: 0.5270
- F1: 0.5089
- Combined Score: 0.5179

## 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 | F1     | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.5301        | 1.0   | 15   | 0.5200          | 0.3162   | 0.0    | 0.1581         |
| 0.5164        | 2.0   | 30   | 0.5159          | 0.3162   | 0.0    | 0.1581         |
| 0.4983        | 3.0   | 45   | 0.5141          | 0.4657   | 0.4076 | 0.4366         |
| 0.4715        | 4.0   | 60   | 0.5215          | 0.6642   | 0.7187 | 0.6915         |
| 0.4454        | 5.0   | 75   | 0.4973          | 0.5270   | 0.5089 | 0.5179         |
| 0.4184        | 6.0   | 90   | 0.4984          | 0.5711   | 0.5803 | 0.5757         |
| 0.4027        | 7.0   | 105  | 0.5033          | 0.6152   | 0.6424 | 0.6288         |
| 0.399         | 8.0   | 120  | 0.5095          | 0.7230   | 0.7797 | 0.7514         |
| 0.3975        | 9.0   | 135  | 0.5087          | 0.6176   | 0.6486 | 0.6331         |
| 0.3979        | 10.0  | 150  | 0.5088          | 0.7010   | 0.7579 | 0.7295         |


### Framework versions

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