---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: distilbert_sa_GLUE_Experiment_logit_kd_mrpc_384
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MRPC
      type: glue
      config: mrpc
      split: validation
      args: mrpc
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.32598039215686275
    - name: F1
      type: f1
      value: 0.03508771929824561
---

<!-- 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. -->

# distilbert_sa_GLUE_Experiment_logit_kd_mrpc_384

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: 0.5217
- Accuracy: 0.3260
- F1: 0.0351
- Combined Score: 0.1805

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.5343        | 1.0   | 15   | 0.5288          | 0.3162   | 0.0    | 0.1581         |
| 0.5306        | 2.0   | 30   | 0.5289          | 0.3162   | 0.0    | 0.1581         |
| 0.5294        | 3.0   | 45   | 0.5281          | 0.3162   | 0.0    | 0.1581         |
| 0.5277        | 4.0   | 60   | 0.5269          | 0.3162   | 0.0    | 0.1581         |
| 0.518         | 5.0   | 75   | 0.5217          | 0.3260   | 0.0351 | 0.1805         |
| 0.5035        | 6.0   | 90   | 0.5230          | 0.3971   | 0.2635 | 0.3303         |
| 0.4866        | 7.0   | 105  | 0.5301          | 0.3652   | 0.1618 | 0.2635         |
| 0.4624        | 8.0   | 120  | 0.5491          | 0.5147   | 0.5123 | 0.5135         |
| 0.4424        | 9.0   | 135  | 0.5479          | 0.5245   | 0.5530 | 0.5388         |
| 0.4295        | 10.0  | 150  | 0.5660          | 0.5392   | 0.5766 | 0.5579         |


### Framework versions

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