---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: smalldata-microsoft-deberta-base-mnli-eng-only-sentiment-single-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. -->

# smalldata-microsoft-deberta-base-mnli-eng-only-sentiment-single-finetuned-memes

This model is a fine-tuned version of [jayantapaul888/twitter-data-microsoft-deberta-base-mnli-sentiment-finetuned-memes](https://huggingface.co/jayantapaul888/twitter-data-microsoft-deberta-base-mnli-sentiment-finetuned-memes) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7400
- Accuracy: 0.8816
- Precision: 0.8946
- Recall: 0.8937
- F1: 0.8937

## 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: 32
- eval_batch_size: 32
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 378  | 0.2962          | 0.8764   | 0.8917    | 0.8881 | 0.8884 |
| 0.3387        | 2.0   | 756  | 0.2803          | 0.8831   | 0.8950    | 0.8942 | 0.8946 |
| 0.1693        | 3.0   | 1134 | 0.4289          | 0.8764   | 0.8912    | 0.8892 | 0.8886 |
| 0.0772        | 4.0   | 1512 | 0.5436          | 0.8690   | 0.8822    | 0.8823 | 0.8822 |
| 0.0772        | 5.0   | 1890 | 0.6566          | 0.8831   | 0.8960    | 0.8947 | 0.8949 |
| 0.024         | 6.0   | 2268 | 0.7400          | 0.8816   | 0.8946    | 0.8937 | 0.8937 |


### Framework versions

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