---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: twitter-data-distilbert-base-uncased-sentiment-finetuned-memes
  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. -->

# twitter-data-distilbert-base-uncased-sentiment-finetuned-memes

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: 0.2605
- Accuracy: 0.9316
- Precision: 0.9322
- Recall: 0.9316
- F1: 0.9317

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.3463        | 1.0   | 1783  | 0.2966          | 0.9065   | 0.9079    | 0.9065 | 0.9066 |
| 0.2601        | 2.0   | 3566  | 0.2526          | 0.9245   | 0.9254    | 0.9245 | 0.9244 |
| 0.2228        | 3.0   | 5349  | 0.2355          | 0.9313   | 0.9327    | 0.9313 | 0.9314 |
| 0.1997        | 4.0   | 7132  | 0.2243          | 0.9341   | 0.9354    | 0.9341 | 0.9342 |
| 0.1779        | 5.0   | 8915  | 0.2254          | 0.9346   | 0.9354    | 0.9346 | 0.9345 |
| 0.1642        | 6.0   | 10698 | 0.2355          | 0.9322   | 0.9329    | 0.9322 | 0.9323 |
| 0.146         | 7.0   | 12481 | 0.2485          | 0.9302   | 0.9306    | 0.9302 | 0.9303 |
| 0.1368        | 8.0   | 14264 | 0.2530          | 0.9296   | 0.9312    | 0.9296 | 0.9299 |
| 0.1293        | 9.0   | 16047 | 0.2585          | 0.9317   | 0.9322    | 0.9317 | 0.9317 |
| 0.121         | 10.0  | 17830 | 0.2605          | 0.9316   | 0.9322    | 0.9316 | 0.9317 |


### Framework versions

- Transformers 4.24.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.6.1
- Tokenizers 0.13.1