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---
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