Instructions to use promforge/working with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use promforge/working with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="promforge/working")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("promforge/working") model = AutoModelForSequenceClassification.from_pretrained("promforge/working", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Sharuka Thirimanne commited on
Training in progress, epoch 2
Browse files- model.safetensors +1 -1
- runs/Apr10_14-58-13_9088970cc926/events.out.tfevents.1712761095.9088970cc926.34.0 +2 -2
- wandb/debug-internal.log +25 -0
- wandb/run-20240410_150123-cuua991r/files/output.log +2 -0
- wandb/run-20240410_150123-cuua991r/files/wandb-summary.json +1 -1
- wandb/run-20240410_150123-cuua991r/logs/debug-internal.log +25 -0
- wandb/run-20240410_150123-cuua991r/run-cuua991r.wandb +0 -0
model.safetensors
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/opt/conda/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
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{"train/loss": 1.8337, "train/grad_norm": 8.119162559509277, "train/learning_rate": 1.2033898305084745e-05, "train/epoch": 2.0, "train/global_step": 236, "_timestamp": 1712761419.6800258, "_runtime": 136.12929391860962, "_step": 3, "eval/loss": 1.8552484512329102, "eval/accuracy": 0.2605633802816901, "eval/precision": 0.229201952219647, "eval/recall": 0.2605633802816901, "eval/f1": 0.20020510365383345, "eval/runtime": 2.8426, "eval/samples_per_second": 49.954, "eval/steps_per_second": 6.332}
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