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distilbert-tweet_eval-emotion
max-gartz/distilbert-tweet_eval-emotion
distilbert-tweet_eval-emotion is a text classification model from max-gartz. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Feb 14, 2024
- Updated
- Feb 15, 2024
- SHA
- d070cd47
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Base models
Model card
From the Hugging Face model README
<!-- 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-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
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Feb 14, 2024
- Updated
- Feb 15, 2024