metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- tweet_eval
metrics:
- f1
base_model: distilbert-base-uncased
model-index:
- name: hate_trained
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: tweet_eval
type: tweet_eval
args: hate
metrics:
- type: f1
value: 0.7730369969869401
name: F1
hate_trained
This model is a fine-tuned version of distilbert-base-uncased on the tweet_eval dataset. It achieves the following results on the evaluation set:
- Loss: 0.9661
- F1: 0.7730
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: 9.303025140957233e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 0
- 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 |
|---|---|---|---|---|
| 0.4767 | 1.0 | 2250 | 0.5334 | 0.7717 |
| 0.4342 | 2.0 | 4500 | 0.7633 | 0.7627 |
| 0.3813 | 3.0 | 6750 | 0.9452 | 0.7614 |
| 0.3118 | 4.0 | 9000 | 0.9661 | 0.7730 |
Framework versions
- Transformers 4.13.0
- Pytorch 1.10.0+cu111
- Datasets 1.16.1
- Tokenizers 0.10.3