Text Classification
Transformers
TensorBoard
Safetensors
modernbert
Generated from Trainer
text-embeddings-inference
Instructions to use esekeroglu/ModernBERT-domain-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use esekeroglu/ModernBERT-domain-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="esekeroglu/ModernBERT-domain-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("esekeroglu/ModernBERT-domain-classifier") model = AutoModelForSequenceClassification.from_pretrained("esekeroglu/ModernBERT-domain-classifier") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files
README.md
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This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-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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- F1: 0.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | F1 |
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| No log | 1.0 | 29 | 0.
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| No log | 2.0 | 58 | 0.
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| No log | 3.0 | 87 | 0.
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### Framework versions
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This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2692
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- F1: 0.9410
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| No log | 1.0 | 29 | 0.8435 | 0.8299 |
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| No log | 2.0 | 58 | 0.3284 | 0.9134 |
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| No log | 3.0 | 87 | 0.3300 | 0.9084 |
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| 0.8422 | 4.0 | 116 | 0.3164 | 0.9143 |
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| 0.8422 | 5.0 | 145 | 0.2692 | 0.9410 |
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### Framework versions
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model.safetensors
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runs/Jan29_15-01-06_EmreSekeroglu/events.out.tfevents.1738152068.EmreSekeroglu.4008.0
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training_args.bin
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