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# distilbert-base-uncased-finetuned-tweet_hate

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: 0.6390
- Accuracy: 0.77
- F1: 0.7712

## 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: 32
- eval_batch_size: 32
- 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 | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.5003        | 1.0   | 282  | 0.4716          | 0.76     | 0.7613 |
| 0.3428        | 2.0   | 564  | 0.4767          | 0.771    | 0.7721 |
| 0.2559        | 3.0   | 846  | 0.5256          | 0.778    | 0.7789 |
| 0.1811        | 4.0   | 1128 | 0.5839          | 0.774    | 0.7748 |
| 0.134         | 5.0   | 1410 | 0.6390          | 0.77     | 0.7712 |


### Framework versions

- Transformers 4.16.2
- Pytorch 2.1.0+cu121
- Datasets 1.16.1
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["tweet_eval"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "distilbert-base-uncased-finetuned-tweet_hate", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "tweet_eval", "type": "tweet_eval", "args": "hate"}, "metrics": [{"type": "accuracy", "value": 0.77, "name": "Accuracy"}, {"type": "f1", "value": 0.7711956429754464, "name": "F1"}]}]}]}
transformers pytorch tensorboard distilbert text-classification generated_from_trainer dataset:tweet_eval license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us