---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- tweet_eval
metrics:
- accuracy
- f1
model-index:
- name: tiny-mlm-imdb-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: 0.6925133689839572
    - name: F1
      type: f1
      value: 0.7003562110650444
---

<!-- 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. -->

# tiny-mlm-imdb-target-tweet

This model is a fine-tuned version of [muhtasham/tiny-mlm-imdb](https://huggingface.co/muhtasham/tiny-mlm-imdb) on the tweet_eval dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5550
- Accuracy: 0.6925
- F1: 0.7004

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.159         | 4.9   | 500  | 0.9977          | 0.6364   | 0.6013 |
| 0.7514        | 9.8   | 1000 | 0.8549          | 0.7112   | 0.7026 |
| 0.5011        | 14.71 | 1500 | 0.8516          | 0.7032   | 0.6962 |
| 0.34          | 19.61 | 2000 | 0.9019          | 0.7059   | 0.7030 |
| 0.2258        | 24.51 | 2500 | 0.9722          | 0.7166   | 0.7164 |
| 0.1607        | 29.41 | 3000 | 1.0724          | 0.6979   | 0.6999 |
| 0.1127        | 34.31 | 3500 | 1.1435          | 0.7193   | 0.7169 |
| 0.0791        | 39.22 | 4000 | 1.2807          | 0.7059   | 0.7069 |
| 0.0568        | 44.12 | 4500 | 1.3849          | 0.7139   | 0.7159 |
| 0.0478        | 49.02 | 5000 | 1.5550          | 0.6925   | 0.7004 |


### Framework versions

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