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

This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2474
- Accuracy: 0.9282
- Precision: 0.9290
- Recall: 0.9282
- F1: 0.9282

## 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: 6

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.3623        | 1.0   | 1762  | 0.3171          | 0.8986   | 0.8995    | 0.8986 | 0.8981 |
| 0.271         | 2.0   | 3524  | 0.2665          | 0.9176   | 0.9182    | 0.9176 | 0.9173 |
| 0.2386        | 3.0   | 5286  | 0.2499          | 0.9237   | 0.9254    | 0.9237 | 0.9239 |
| 0.2136        | 4.0   | 7048  | 0.2494          | 0.9259   | 0.9263    | 0.9259 | 0.9257 |
| 0.1974        | 5.0   | 8810  | 0.2454          | 0.9278   | 0.9288    | 0.9278 | 0.9278 |
| 0.182         | 6.0   | 10572 | 0.2474          | 0.9282   | 0.9290    | 0.9282 | 0.9282 |


### Framework versions

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