transformers pytorch tensorboard distilbert text-classification generated_from_trainer dataset:glue license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- glue
license: apache-2.0
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: Glue_distilbert_new
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: glue
      type: glue
      config: mrpc
      split: validation
      args: mrpc
    metrics:
    - type: accuracy
      value: 0.6397058823529411
      name: Accuracy
    - type: f1
      value: 0.7360861759425494
      name: F1
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# Glue_distilbert_new

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6153
- Accuracy: 0.6397
- F1: 0.7361
- Combined Score: 0.6879

## 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: 1024
- eval_batch_size: 1024
- seed: 33
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6415        | 1.0   | 4    | 0.6363          | 0.6838   | 0.8122 | 0.7480         |
| 0.6292        | 2.0   | 8    | 0.6101          | 0.6838   | 0.8122 | 0.7480         |
| 0.6244        | 3.0   | 12   | 0.6047          | 0.6838   | 0.8122 | 0.7480         |
| 0.6075        | 4.0   | 16   | 0.6153          | 0.6397   | 0.7361 | 0.6879         |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.11.6
