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
- f1
tags:
- generated_from_trainer
model-index:
- name: distilbert_add_GLUE_Experiment_logit_kd_mrpc_96
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE MRPC
      type: glue
      config: mrpc
      split: validation
      args: mrpc
    metrics:
    - type: accuracy
      value: 0.3161764705882353
      name: Accuracy
    - type: f1
      value: 0.0
      name: F1
---

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# distilbert_add_GLUE_Experiment_logit_kd_mrpc_96

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5290
- Accuracy: 0.3162
- F1: 0.0
- Combined Score: 0.1581

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|:--------------:|
| 0.5436        | 1.0   | 15   | 0.5321          | 0.3162   | 0.0 | 0.1581         |
| 0.5318        | 2.0   | 30   | 0.5297          | 0.3162   | 0.0 | 0.1581         |
| 0.5299        | 3.0   | 45   | 0.5290          | 0.3162   | 0.0 | 0.1581         |
| 0.529         | 4.0   | 60   | 0.5293          | 0.3162   | 0.0 | 0.1581         |
| 0.5278        | 5.0   | 75   | 0.5290          | 0.3162   | 0.0 | 0.1581         |
| 0.5294        | 6.0   | 90   | 0.5291          | 0.3162   | 0.0 | 0.1581         |
| 0.5274        | 7.0   | 105  | 0.5292          | 0.3162   | 0.0 | 0.1581         |
| 0.5286        | 8.0   | 120  | 0.5290          | 0.3162   | 0.0 | 0.1581         |


### Framework versions

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