Text Classification
Transformers
Safetensors
English
roberta
distilroberta
climate
text-embeddings-inference
Instructions to use maai-project/maai-frame-sl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maai-project/maai-frame-sl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="maai-project/maai-frame-sl")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("maai-project/maai-frame-sl") model = AutoModelForSequenceClassification.from_pretrained("maai-project/maai-frame-sl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload test_metrics.json with huggingface_hub
Browse files- test_metrics.json +61 -0
test_metrics.json
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{
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"accuracy": 0.6656151419558359,
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"macro_f1": 0.6102499559979805,
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"report": {
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"0": {
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"precision": 0.6892857142857143,
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"f1-score": 0.6620926243567753,
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"support": 303.0
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},
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"1": {
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"precision": 0.6580882352941176,
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"recall": 0.6415770609318996,
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"support": 279.0
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},
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"2": {
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"recall": 0.6263736263736264,
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"support": 182.0
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},
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"3": {
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"recall": 0.425,
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"f1-score": 0.4811320754716981,
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"support": 120.0
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},
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"4": {
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"recall": 0.48226950354609927,
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"f1-score": 0.5074626865671642,
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"support": 141.0
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},
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"5": {
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"precision": 0.7462277091906722,
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"recall": 0.7816091954022989,
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"f1-score": 0.7635087719298246,
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"support": 696.0
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},
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"6": {
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"recall": 0.6464088397790055,
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"f1-score": 0.6046511627906976,
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"support": 181.0
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},
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"accuracy": 0.6656151419558359,
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"macro avg": {
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"precision": 0.6189966248333386,
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"recall": 0.6057431317717951,
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"f1-score": 0.6102499559979805,
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"support": 1902.0
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},
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"weighted avg": {
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"precision": 0.6637805418116866,
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"recall": 0.6656151419558359,
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"f1-score": 0.6634058589567094,
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"support": 1902.0
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}
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}
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}
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