Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use hermanda/robeczech-propaganda with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hermanda/robeczech-propaganda with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hermanda/robeczech-propaganda")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hermanda/robeczech-propaganda") model = AutoModelForSequenceClassification.from_pretrained("hermanda/robeczech-propaganda", device_map="auto") - Notebooks
- Google Colab
- Kaggle
v4: 27k training data, all layers, class_weight=3.0, lr=1e-5, early_stop on loss
Browse files- README.md +8 -9
- model.safetensors +1 -1
- training_args.bin +1 -1
README.md
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This model is a fine-tuned version of [ufal/robeczech-base](https://huggingface.co/ufal/robeczech-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Recall: 0.
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- F1: 0.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
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| 0.3050 | 5.0 | 1495 | 0.5046 | 0.4419 | 0.5808 | 0.5019 |
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### Framework versions
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This model is a fine-tuned version of [ufal/robeczech-base](https://huggingface.co/ufal/robeczech-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4071
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- Precision: 0.4632
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- Recall: 0.7785
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- F1: 0.5808
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
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| 0.5118 | 1.0 | 724 | 0.4468 | 0.4103 | 0.7817 | 0.5381 |
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| 0.4224 | 2.0 | 1448 | 0.4072 | 0.4606 | 0.7785 | 0.5788 |
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| 0.3386 | 3.0 | 2172 | 0.4164 | 0.4773 | 0.7271 | 0.5763 |
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| 0.3071 | 4.0 | 2896 | 0.4635 | 0.5221 | 0.6453 | 0.5772 |
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### Framework versions
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model.safetensors
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training_args.bin
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