---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- tweet_eval
metrics:
- accuracy
- f1
model-index:
- name: medium-mlm-tweet-target-tweet
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: tweet_eval
      type: tweet_eval
      config: emotion
      split: train
      args: emotion
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7593582887700535
    - name: F1
      type: f1
      value: 0.7637254221785755
---

<!-- 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. -->

# medium-mlm-tweet-target-tweet

This model is a fine-tuned version of [muhtasham/medium-mlm-tweet](https://huggingface.co/muhtasham/medium-mlm-tweet) on the tweet_eval dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9066
- Accuracy: 0.7594
- F1: 0.7637

## 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: 3e-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: constant
- num_epochs: 200

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.4702        | 4.9   | 500  | 0.8711          | 0.7540   | 0.7532 |
| 0.0629        | 9.8   | 1000 | 1.2918          | 0.7701   | 0.7668 |
| 0.0227        | 14.71 | 1500 | 1.4801          | 0.7727   | 0.7696 |
| 0.0181        | 19.61 | 2000 | 1.5118          | 0.7888   | 0.7870 |
| 0.0114        | 24.51 | 2500 | 1.6747          | 0.7754   | 0.7745 |
| 0.0141        | 29.41 | 3000 | 1.8765          | 0.7674   | 0.7628 |
| 0.0177        | 34.31 | 3500 | 1.9066          | 0.7594   | 0.7637 |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.7.1
- Tokenizers 0.13.2