Instructions to use sharkMeow/train_V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sharkMeow/train_V2 with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("sharkMeow/train_V2") model = AutoModel.from_pretrained("sharkMeow/train_V2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files- all_results.json +6 -6
- train_results.json +6 -6
- trainer_state.json +0 -0
all_results.json
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"epoch":
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"train_loss":
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{
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"epoch": 99.89819919147372,
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"total_flos": 3.5659868061024707e+18,
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"train_loss": 1.3533928022805382,
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"train_runtime": 51839.0624,
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"train_samples_per_second": 262.435,
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"train_steps_per_second": 1.312
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train_results.json
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"epoch":
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"train_runtime":
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"train_samples_per_second":
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"train_steps_per_second":
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{
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"epoch": 99.89819919147372,
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"total_flos": 3.5659868061024707e+18,
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"train_loss": 1.3533928022805382,
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"train_runtime": 51839.0624,
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"train_samples_per_second": 262.435,
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"train_steps_per_second": 1.312
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}
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trainer_state.json
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