Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Rexhaif/rubert-base-srl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rexhaif/rubert-base-srl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Rexhaif/rubert-base-srl")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Rexhaif/rubert-base-srl") model = AutoModelForSequenceClassification.from_pretrained("Rexhaif/rubert-base-srl") - Notebooks
- Google Colab
- Kaggle
Daniil Larionov commited on
fixing gpg
Browse files- eval_results.json +3 -3
eval_results.json
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{
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"epoch": 10.0,
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"eval_f1": 0.
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"eval_loss": 0.
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"eval_runtime": 0.4749,
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"eval_samples": 101,
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"eval_samples_per_second": 212.677,
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"eval_steps_per_second": 27.374
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}
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{
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"epoch": 10.0,
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"eval_f1": 0.9562,
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"eval_loss": 0.2428,
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"eval_runtime": 0.4749,
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"eval_samples": 101,
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"eval_samples_per_second": 212.677,
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"eval_steps_per_second": 27.374
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}
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