---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- tweet_eval
metrics:
- f1
base_model: distilbert-base-uncased
model-index:
- name: presentation_irony_1234567
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: tweet_eval
      type: tweet_eval
      args: irony
    metrics:
    - type: f1
      value: 0.674604535422547
      name: F1
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# presentation_irony_1234567

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the tweet_eval dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9493
- F1: 0.6746

## 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: 5.1637764704815665e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 1234567
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.5514        | 1.0   | 90   | 0.5917          | 0.6767 |
| 0.6107        | 2.0   | 180  | 0.6123          | 0.6730 |
| 0.1327        | 3.0   | 270  | 0.7463          | 0.6970 |
| 0.1068        | 4.0   | 360  | 0.9493          | 0.6746 |


### Framework versions

- Transformers 4.12.5
- Pytorch 1.9.1
- Datasets 1.16.1
- Tokenizers 0.10.3