Commit From AutoTrain
Browse files- .gitattributes +3 -0
- README.md +56 -0
- config.json +43 -0
- pytorch_model.bin +3 -0
- sentencepiece.bpe.model +3 -0
- special_tokens_map.json +15 -0
- tokenizer.json +3 -0
- tokenizer_config.json +20 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.bin.* filter=lfs diff=lfs merge=lfs -text
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*.tar.gz filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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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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- Muhsabrys/autotrain-data-xlmroberta-iuexist
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co2_eq_emissions:
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emissions: 1.1811615672607385
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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: 50302120401
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- CO2 Emissions (in grams): 1.1812
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## Validation Metrics
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- Loss: 0.637
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- Accuracy: 0.772
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- Macro F1: 0.541
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- Micro F1: 0.772
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- Weighted F1: 0.731
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- Macro Precision: 0.514
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- Micro Precision: 0.772
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- Weighted Precision: 0.694
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- Macro Recall: 0.571
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- Micro Recall: 0.772
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- Weighted Recall: 0.772
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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/Muhsabrys/autotrain-xlmroberta-iuexist-50302120401
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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("Muhsabrys/autotrain-xlmroberta-iuexist-50302120401", use_auth_token=True)
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tokenizer = AutoTokenizer.from_pretrained("Muhsabrys/autotrain-xlmroberta-iuexist-50302120401", 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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{
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"_name_or_path": "AutoTrain",
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"_num_labels": 3,
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"architectures": [
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"XLMRobertaForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"bos_token_id": 0,
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"classifier_dropout": null,
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"eos_token_id": 2,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "0",
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"1": "1",
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"2": "99"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"0": 0,
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"1": 1,
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"99": 2
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},
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"layer_norm_eps": 1e-05,
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"max_length": 96,
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"max_position_embeddings": 514,
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"model_type": "xlm-roberta",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"output_past": true,
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"pad_token_id": 1,
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"padding": "max_length",
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"torch_dtype": "float32",
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"transformers_version": "4.25.1",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 250002
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:ae983b6002a58c66a016be35c7f90c6266cadd2220133e050ff39d3da8c86e8d
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size 1112257205
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sentencepiece.bpe.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:cfc8146abe2a0488e9e2a0c56de7952f7c11ab059eca145a0a727afce0db2865
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size 5069051
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special_tokens_map.json
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{
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"bos_token": "<s>",
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"cls_token": "<s>",
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"eos_token": "</s>",
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"mask_token": {
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"content": "<mask>",
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"lstrip": true,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": "<pad>",
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"sep_token": "</s>",
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"unk_token": "<unk>"
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}
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:c39c9bbca9b0d0df983e89cdce08c69d804c14c7426761de6bea563eab01c972
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size 17082923
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tokenizer_config.json
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{
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"bos_token": "<s>",
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"cls_token": "<s>",
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"eos_token": "</s>",
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"mask_token": {
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"__type": "AddedToken",
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"content": "<mask>",
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"lstrip": true,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"model_max_length": 1000000000000000019884624838656,
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"name_or_path": "AutoTrain",
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"pad_token": "<pad>",
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"sep_token": "</s>",
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"special_tokens_map_file": null,
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"tokenizer_class": "XLMRobertaTokenizer",
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"unk_token": "<unk>"
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}
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