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roberta-large-go-emotions_v2
Prasadrao/roberta-large-go-emotions_v2
roberta-large-go-emotions_v2 is a text classification model from Prasadrao. 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
- roberta
- Access
- Public
- Created
- Feb 24, 2024
- Updated
- Feb 25, 2024
- SHA
- 57c7f1d2
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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. -->
roberta-large-go-emotions_v2
This model is a fine-tuned version of Prasadrao/roberta-large-go-emotions on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0952
- Accuracy: 0.4613
- Precision: 0.5326
- Recall: 0.5126
- F1: 0.5165
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: 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 | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 679 | 0.0844 | 0.4552 | 0.5190 | 0.5026 | 0.4984 |
| 0.0647 | 2.0 | 1358 | 0.0866 | 0.4449 | 0.5308 | 0.5100 | 0.5063 |
| 0.0647 | 3.0 | 2037 | 0.0898 | 0.4471 | 0.5261 | 0.5253 | 0.5166 |
| 0.0473 | 4.0 | 2716 | 0.0952 | 0.4613 | 0.5326 | 0.5126 | 0.5165 |
Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.15.0
- Tokenizers 0.15.1
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Feb 24, 2024
- Updated
- Feb 25, 2024