Text Classification
Transformers
TensorBoard
Safetensors
bert
Trained with AutoTrain
text-embeddings-inference
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("Meylai/ai-model-try-out")
model = AutoModelForSequenceClassification.from_pretrained("Meylai/ai-model-try-out")Quick Links
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 1.0107622146606445
f1_macro: 0.27777777777777773
f1_micro: 0.4
f1_weighted: 0.3416666666666667
precision_macro: 0.26666666666666666
precision_micro: 0.4
precision_weighted: 0.32
recall_macro: 0.31746031746031744
recall_micro: 0.4
recall_weighted: 0.4
accuracy: 0.4
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Model tree for Meylai/ai-model-try-out
Base model
google-bert/bert-base-uncased
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Meylai/ai-model-try-out")