metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- tweet_eval
metrics:
- f1
model-index:
- name: presentation_sentiment_42
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: tweet_eval
type: tweet_eval
args: sentiment
metrics:
- name: F1
type: f1
value: 0.7175864613336908
presentation_sentiment_42
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: 0.6491
- F1: 0.7176
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: 6.923967812567773e-06
- 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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.4391 | 1.0 | 2851 | 0.6591 | 0.6953 |
| 0.6288 | 2.0 | 5702 | 0.6265 | 0.7158 |
| 0.4071 | 3.0 | 8553 | 0.6401 | 0.7179 |
| 0.6532 | 4.0 | 11404 | 0.6491 | 0.7176 |
Framework versions
- Transformers 4.12.5
- Pytorch 1.9.1
- Datasets 1.16.1
- Tokenizers 0.10.3