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 470
Browse files- model.safetensors +1 -1
- training_log.csv +2 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:4d2f56b94e931799915656b92b24427e12c13d438c4c390f84f42979c764ff74
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training_log.csv
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467.0,0.3502601359139448,0.7232545463554829,0.14702273905277252,14.3723,179.025,5.636,0.26000777302759426,307286
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| 469 |
468.0,0.3483765779964437,0.7232395414619622,0.14697112143039703,14.1945,181.268,5.706,0.25884181888845703,307944
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| 470 |
469.0,0.3479286662488523,0.7228592702903947,0.14699943363666534,14.4776,177.723,5.595,0.25845316750874464,308602
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| 468 |
467.0,0.3502601359139448,0.7232545463554829,0.14702273905277252,14.3723,179.025,5.636,0.26000777302759426,307286
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| 469 |
468.0,0.3483765779964437,0.7232395414619622,0.14697112143039703,14.1945,181.268,5.706,0.25884181888845703,307944
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| 470 |
469.0,0.3479286662488523,0.7228592702903947,0.14699943363666534,14.4776,177.723,5.595,0.25845316750874464,308602
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| 471 |
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470.0,0.3489884287433366,0.7230028300481605,0.1469458043575287,14.49,177.571,5.59,0.26078507578701904,309260
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| 472 |
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471.0,0.34825932529275966,0.7228700441621595,0.14697134494781494,14.2477,180.591,5.685,0.25961912164788187,309918
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