negative positive
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__sst2__train-8-2
  results: []
---

<!-- 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-base-uncased__sst2__train-8-2

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6932
- Accuracy: 0.4931

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7081        | 1.0   | 3    | 0.7031          | 0.25     |
| 0.6853        | 2.0   | 6    | 0.7109          | 0.25     |
| 0.6696        | 3.0   | 9    | 0.7211          | 0.25     |
| 0.6174        | 4.0   | 12   | 0.7407          | 0.25     |
| 0.5717        | 5.0   | 15   | 0.7625          | 0.25     |
| 0.5096        | 6.0   | 18   | 0.7732          | 0.25     |
| 0.488         | 7.0   | 21   | 0.7798          | 0.25     |
| 0.4023        | 8.0   | 24   | 0.7981          | 0.25     |
| 0.3556        | 9.0   | 27   | 0.8110          | 0.25     |
| 0.2714        | 10.0  | 30   | 0.8269          | 0.25     |
| 0.2295        | 11.0  | 33   | 0.8276          | 0.25     |


### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3
