Instructions to use bappaiitj/mlops-assignment3_final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bappaiitj/mlops-assignment3_final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bappaiitj/mlops-assignment3_final")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bappaiitj/mlops-assignment3_final") model = AutoModelForSequenceClassification.from_pretrained("bappaiitj/mlops-assignment3_final") - Notebooks
- Google Colab
- Kaggle
Upload train_metrics.json with huggingface_hub
Browse files- train_metrics.json +8 -0
train_metrics.json
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{
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"train_runtime": 168.4535,
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"train_samples_per_second": 113.978,
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"train_steps_per_second": 14.247,
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"total_flos": 635911549747200.0,
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"train_loss": 1.1017762994766236,
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"epoch": 3.0
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}
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