---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- tweet_eval
metrics:
- accuracy
model-index:
- name: distilbert-base-cased-finetuned-tweeteval
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: tweet_eval
      type: tweet_eval
      config: emotion
      split: validation
      args: emotion
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7887700534759359
---

<!-- 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. -->

# distilbert-base-cased-finetuned-tweeteval

This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the tweet_eval dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7720
- Accuracy: 0.7888

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 204  | 0.6867          | 0.7647   |
| No log        | 2.0   | 408  | 0.6318          | 0.7968   |
| 0.6397        | 3.0   | 612  | 0.6931          | 0.7834   |
| 0.6397        | 4.0   | 816  | 0.7631          | 0.7754   |
| 0.2064        | 5.0   | 1020 | 0.7720          | 0.7888   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3