---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- tweet_eval
metrics:
- accuracy
- f1
model-index:
- name: base-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: 0.7754010695187166
    - name: F1
      type: f1
      value: 0.77889743305892
---

<!-- 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. -->

# base-mlm-imdb-target-tweet

This model is a fine-tuned version of [muhtasham/base-mlm-imdb](https://huggingface.co/muhtasham/base-mlm-imdb) on the tweet_eval dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7516
- Accuracy: 0.7754
- F1: 0.7789

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.3412        | 4.9   | 500  | 1.0525          | 0.7888   | 0.7891 |
| 0.0365        | 9.8   | 1000 | 1.4590          | 0.7540   | 0.7572 |
| 0.0127        | 14.71 | 1500 | 1.4788          | 0.7888   | 0.7890 |
| 0.0137        | 19.61 | 2000 | 1.7516          | 0.7754   | 0.7789 |


### Framework versions

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