---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: twitter-data-microsoft-xtremedistil-l6-h256-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-microsoft-xtremedistil-l6-h256-uncased-sentiment-finetuned-memes

This model is a fine-tuned version of [microsoft/xtremedistil-l6-h256-uncased](https://huggingface.co/microsoft/xtremedistil-l6-h256-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3635
- Accuracy: 0.8756
- Precision: 0.8761
- Recall: 0.8756
- F1: 0.8755

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.6142        | 1.0   | 1762  | 0.5396          | 0.8022   | 0.8010    | 0.8022 | 0.8014 |
| 0.4911        | 2.0   | 3524  | 0.4588          | 0.8322   | 0.8332    | 0.8322 | 0.8325 |
| 0.4511        | 3.0   | 5286  | 0.4072          | 0.8562   | 0.8564    | 0.8562 | 0.8559 |
| 0.412         | 4.0   | 7048  | 0.3825          | 0.8673   | 0.8680    | 0.8673 | 0.8672 |
| 0.3886        | 5.0   | 8810  | 0.3677          | 0.8745   | 0.8753    | 0.8745 | 0.8745 |
| 0.3914        | 6.0   | 10572 | 0.3635          | 0.8756   | 0.8761    | 0.8756 | 0.8755 |


### Framework versions

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