Text Classification
Transformers
Safetensors
Russian
customer-support
hierarchical-classification
mps
minilm
Instructions to use ZenMan67/support-ticket-classifiers-minilm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZenMan67/support-ticket-classifiers-minilm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ZenMan67/support-ticket-classifiers-minilm")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ZenMan67/support-ticket-classifiers-minilm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "task": "handler", | |
| "best_epoch": 5, | |
| "training_seconds": 304.73208945803344, | |
| "split_sizes": { | |
| "train": 2400, | |
| "validation": 300, | |
| "test": 300 | |
| }, | |
| "validation": { | |
| "loss": 0.5876449354489645, | |
| "accuracy": 0.8466666666666667, | |
| "macro_f1": 0.8471922277069336 | |
| }, | |
| "test": { | |
| "loss": 0.6294241340955099, | |
| "accuracy": 0.8166666666666667, | |
| "macro_f1": 0.816800011054457 | |
| }, | |
| "test_confusions": [ | |
| { | |
| "gold": "human", | |
| "predicted": "llm", | |
| "count": 18 | |
| }, | |
| { | |
| "gold": "llm", | |
| "predicted": "auto", | |
| "count": 15 | |
| }, | |
| { | |
| "gold": "llm", | |
| "predicted": "human", | |
| "count": 10 | |
| }, | |
| { | |
| "gold": "auto", | |
| "predicted": "llm", | |
| "count": 5 | |
| }, | |
| { | |
| "gold": "auto", | |
| "predicted": "human", | |
| "count": 5 | |
| }, | |
| { | |
| "gold": "human", | |
| "predicted": "auto", | |
| "count": 2 | |
| } | |
| ], | |
| "history": [ | |
| { | |
| "epoch": 1, | |
| "train_loss": 0.9450590944290161, | |
| "validation_loss": 0.640375197728475, | |
| "validation_accuracy": 0.7833333333333333, | |
| "validation_macro_f1": 0.7873895322407908 | |
| }, | |
| { | |
| "epoch": 2, | |
| "train_loss": 0.3881728690862656, | |
| "validation_loss": 0.5689977049827576, | |
| "validation_accuracy": 0.8366666666666667, | |
| "validation_macro_f1": 0.8295788111791534 | |
| }, | |
| { | |
| "epoch": 3, | |
| "train_loss": 0.18638452569643657, | |
| "validation_loss": 0.6046478613217672, | |
| "validation_accuracy": 0.8033333333333333, | |
| "validation_macro_f1": 0.8073069144063059 | |
| }, | |
| { | |
| "epoch": 4, | |
| "train_loss": 0.17458565334479015, | |
| "validation_loss": 0.5988235028584799, | |
| "validation_accuracy": 0.8333333333333334, | |
| "validation_macro_f1": 0.8331806628375255 | |
| }, | |
| { | |
| "epoch": 5, | |
| "train_loss": 0.17275874733924865, | |
| "validation_loss": 0.5876449354489645, | |
| "validation_accuracy": 0.8466666666666667, | |
| "validation_macro_f1": 0.8471922277069336 | |
| }, | |
| { | |
| "epoch": 6, | |
| "train_loss": 0.17210762143135072, | |
| "validation_loss": 0.5890995128949483, | |
| "validation_accuracy": 0.84, | |
| "validation_macro_f1": 0.839868859643578 | |
| }, | |
| { | |
| "epoch": 7, | |
| "train_loss": 0.17215188225110373, | |
| "validation_loss": 0.5889288687705994, | |
| "validation_accuracy": 0.84, | |
| "validation_macro_f1": 0.8401046298542054 | |
| }, | |
| { | |
| "epoch": 8, | |
| "train_loss": 0.1719669226805369, | |
| "validation_loss": 0.5910564653078715, | |
| "validation_accuracy": 0.8366666666666667, | |
| "validation_macro_f1": 0.8366387893269615 | |
| } | |
| ] | |
| } | |