Commit From AutoTrain
Browse files- .gitattributes +3 -0
- README.md +56 -0
- config.json +3 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +3 -0
- tokenizer.json +3 -0
- tokenizer_config.json +3 -0
- vocab.txt +0 -0
.gitattributes
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README.md
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---
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tags:
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- autotrain
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- text-classification
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language:
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- unk
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widget:
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- text: "I love AutoTrain 🤗"
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datasets:
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- lewtun/autotrain-data-sphere-emotion
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co2_eq_emissions:
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emissions: 0.02429248200067234
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---
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# Model Trained Using AutoTrain
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- Problem type: Multi-class Classification
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- Model ID: 1565855719
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- CO2 Emissions (in grams): 0.0243
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## Validation Metrics
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- Loss: 0.134
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- Accuracy: 0.943
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- Macro F1: 0.915
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- Micro F1: 0.943
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- Weighted F1: 0.943
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- Macro Precision: 0.911
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- Micro Precision: 0.943
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- Weighted Precision: 0.943
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- Macro Recall: 0.920
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- Micro Recall: 0.943
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- Weighted Recall: 0.943
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## Usage
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You can use cURL to access this model:
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```
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$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/models/lewtun/autotrain-sphere-emotion-1565855719
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```
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Or Python API:
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```
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from transformers import AutoModelForSequenceClassification, AutoTokenizer
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model = AutoModelForSequenceClassification.from_pretrained("lewtun/autotrain-sphere-emotion-1565855719", use_auth_token=True)
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tokenizer = AutoTokenizer.from_pretrained("lewtun/autotrain-sphere-emotion-1565855719", use_auth_token=True)
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inputs = tokenizer("I love AutoTrain", return_tensors="pt")
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outputs = model(**inputs)
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```
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config.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:c4200b80458294f18bb25ef5cdc902534fbb3431ce52c27aa6750ec73266042d
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size 915
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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size 267866609
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special_tokens_map.json
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version https://git-lfs.github.com/spec/v1
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size 125
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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size 711661
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tokenizer_config.json
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version https://git-lfs.github.com/spec/v1
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size 346
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vocab.txt
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