Text Classification
Transformers
Safetensors
English
multilingual
xlm-roberta
multi-label-classification
multi-head-classification
disaster-response
humanitarian-aid
social-media
twitter
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use spencercdz/xlm-roberta-sentiment-requests with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use spencercdz/xlm-roberta-sentiment-requests with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="spencercdz/xlm-roberta-sentiment-requests")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("spencercdz/xlm-roberta-sentiment-requests") model = AutoModel.from_pretrained("spencercdz/xlm-roberta-sentiment-requests") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 380
Browse files- model.safetensors +1 -1
- training_log.csv +1 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:85f2edf6d4e8fbe682d77cedc7105b9f64f7fbc3e84ef1198fcfd3d1b70ef9fe
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training_log.csv
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| 378 |
377.0,0.34497865028006286,0.7213962508080155,0.14744699001312256,14.5538,176.792,5.566,0.25728721336960747,248066
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| 379 |
378.0,0.34493038823053307,0.7215409819788512,0.14753125607967377,14.7292,174.687,5.499,0.25806451612903225,248724
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| 380 |
379.0,0.3436758104008564,0.7211026521371349,0.14746162295341492,14.6841,175.224,5.516,0.25806451612903225,249382
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| 378 |
377.0,0.34497865028006286,0.7213962508080155,0.14744699001312256,14.5538,176.792,5.566,0.25728721336960747,248066
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| 379 |
378.0,0.34493038823053307,0.7215409819788512,0.14753125607967377,14.7292,174.687,5.499,0.25806451612903225,248724
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| 380 |
379.0,0.3436758104008564,0.7211026521371349,0.14746162295341492,14.6841,175.224,5.516,0.25806451612903225,249382
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| 381 |
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380.0,0.34424721585462986,0.7210283388753784,0.14756938815116882,14.459,177.952,5.602,0.2592304702681695,250040
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