metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: distilbert-tweet_eval-emotion
results: []
distilbert-tweet_eval-emotion
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: 0.6404
- Accuracy: 0.6529
- Precision: 0.8110
- Recall: 0.6529
- F1: 0.6507
- Auroc: 0.9184
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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Auroc |
|---|---|---|---|---|---|---|---|---|
| 0.7228 | 0.55 | 500 | 0.7232 | 0.6030 | 0.5625 | 0.6030 | 0.5760 | 0.8937 |
| 0.64 | 1.1 | 1000 | 0.6404 | 0.6529 | 0.8110 | 0.6529 | 0.6507 | 0.9184 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.2
- Datasets 2.17.0
- Tokenizers 0.15.1