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bert-base-multilingual-uncased-finetuned-MeIA-AnalisisDeSentimientos
kevinid/bert-base-multilingual-uncased-finetuned-MeIA-AnalisisDeSentimientos
bert-base-multilingual-uncased-finetuned-MeIA-AnalisisDeSentimientos is a text classification model from kevinid. 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
- bert
- Access
- Public
- Created
- Jun 28, 2023
- Updated
- Jun 29, 2023
- SHA
- 091a5a8a
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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. -->
bert-base-multilingual-uncased-finetuned-MeIA-AnalisisDeSentimientos
This model is a fine-tuned version of bert-base-multilingual-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0342
- F1: 0.5746
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: 2e-05
- 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 |
|---|---|---|---|---|
| 1.0295 | 1.0 | 766 | 1.0167 | 0.5416 |
| 0.9326 | 2.0 | 1532 | 1.0108 | 0.5553 |
| 0.7689 | 3.0 | 2298 | 1.0342 | 0.5746 |
| 0.623 | 4.0 | 3064 | 1.1112 | 0.5679 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Jun 28, 2023
- Updated
- Jun 29, 2023