Instructions to use taniwasl/newspapers_procon_es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use taniwasl/newspapers_procon_es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="taniwasl/newspapers_procon_es")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("taniwasl/newspapers_procon_es") model = AutoModelForSequenceClassification.from_pretrained("taniwasl/newspapers_procon_es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
Model Metrics
- loss: 0.2011
- learning_rate: 0.0
- epoch: 1.5
- step: 348
- eval_loss: 0.25064921379089355
- eval_accuracy: 0.8926850635129215
- eval_runtime: 59.2768
- eval_samples_per_second: 12.838
- eval_steps_per_second: 0.27
- timestamp: 1731213167
- checkpoint_dir_name: checkpoint_000001
- should_checkpoint: True
- done: True
- training_iteration: 2
- trial_id: 4c291_00000
- date: 2024-11-09_20-32-49
- time_this_iter_s: 960.7832322120667
- time_total_s: 1945.5146572589874
- pid: 1245743
- hostname: tani02
- node_ip: 65.21.230.56
- config: {}
- time_since_restore: 1945.5146572589874
- iterations_since_restore: 2
- experiment_tag: 0
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