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scenario-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all
haryoaw/scenario-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all
scenario-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all is a text classification model from haryoaw. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- deberta-v2
- Access
- Public
- Created
- Jul 27, 2024
- Updated
- Jul 27, 2024
- SHA
- 29ba60ca
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Base models
Datasets
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. -->
scenario-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all
This model is a fine-tuned version of microsoft/mdeberta-v3-base on the tweet_sentiment_multilingual dataset. It achieves the following results on the evaluation set:
- Loss: 2.0269
- Accuracy: 0.6362
- F1: 0.6387
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 66
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.8991 | 1.09 | 500 | 0.8258 | 0.6265 | 0.6117 |
| 0.6873 | 2.17 | 1000 | 0.8627 | 0.6481 | 0.6502 |
| 0.5102 | 3.26 | 1500 | 0.9726 | 0.6516 | 0.6440 |
| 0.3825 | 4.35 | 2000 | 1.1881 | 0.6578 | 0.6540 |
| 0.2946 | 5.43 | 2500 | 1.2475 | 0.6532 | 0.6554 |
| 0.228 | 6.52 | 3000 | 1.5294 | 0.6435 | 0.6458 |
| 0.2006 | 7.61 | 3500 | 1.6058 | 0.6389 | 0.6342 |
| 0.159 | 8.7 | 4000 | 1.5956 | 0.6528 | 0.6510 |
| 0.1334 | 9.78 | 4500 | 1.8463 | 0.6478 | 0.6409 |
| 0.1052 | 10.87 | 5000 | 2.0269 | 0.6362 | 0.6387 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- License
- mit
- Created
- Jul 27, 2024
- Updated
- Jul 27, 2024