---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: distilbert_sa_GLUE_Experiment_mnli_384
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MNLI
      type: glue
      config: mnli
      split: validation_matched
      args: mnli
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6144222945484134
---

<!-- 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_mnli_384

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: 0.8561
- Accuracy: 0.6144

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.0075        | 1.0   | 1534  | 0.9587          | 0.5303   |
| 0.9233        | 2.0   | 3068  | 0.9005          | 0.5729   |
| 0.8749        | 3.0   | 4602  | 0.8834          | 0.5888   |
| 0.8389        | 4.0   | 6136  | 0.8564          | 0.6107   |
| 0.8058        | 5.0   | 7670  | 0.8487          | 0.6142   |
| 0.776         | 6.0   | 9204  | 0.8578          | 0.6220   |
| 0.7467        | 7.0   | 10738 | 0.8618          | 0.6187   |
| 0.7171        | 8.0   | 12272 | 0.8828          | 0.6207   |
| 0.6876        | 9.0   | 13806 | 0.8901          | 0.6292   |
| 0.6589        | 10.0  | 15340 | 0.8953          | 0.6219   |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.8.0
- Tokenizers 0.13.2