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 474
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 sha256:86fbd0e9736977c2e476f28f917d30c8fb63788bb54dd38dca718f82ddc66f48
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training_log.csv
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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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| 473 |
472.0,0.34933248159314506,0.723172242874845,0.14698663353919983,14.5791,176.486,5.556,0.25961912164788187,310576
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| 474 |
473.0,0.34757389187751153,0.722820958529923,0.14692862331867218,14.3288,179.568,5.653,0.26039642440730665,311234
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| 472 |
471.0,0.34825932529275966,0.7228700441621595,0.14697134494781494,14.2477,180.591,5.685,0.25961912164788187,309918
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| 473 |
472.0,0.34933248159314506,0.723172242874845,0.14698663353919983,14.5791,176.486,5.556,0.25961912164788187,310576
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| 474 |
473.0,0.34757389187751153,0.722820958529923,0.14692862331867218,14.3288,179.568,5.653,0.26039642440730665,311234
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| 475 |
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474.0,0.34784325961389734,0.7226397252774598,0.1469302624464035,14.5589,176.73,5.564,0.26078507578701904,311892
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| 476 |
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475.0,0.3478697426722473,0.722649848537518,0.1469295173883438,14.6058,176.163,5.546,0.25845316750874464,312550
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