Commit From AutoTrain
Browse files- .gitattributes +3 -0
- README.md +52 -0
- config.json +323 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +7 -0
- tokenizer.json +0 -0
- tokenizer_config.json +14 -0
- vocab.txt +0 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zstandard filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zstandard 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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*.pkl filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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tags: autotrain
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language: unk
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widget:
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- text: "I love AutoTrain 🤗"
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datasets:
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- EXOP/autotrain-data-exop-msc-flat-categories-multilingual
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co2_eq_emissions: 652.3729662301374
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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: 1147942216
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- CO2 Emissions (in grams): 652.3729662301374
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## Validation Metrics
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- Loss: 0.4508252441883087
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- Accuracy: 0.8882102517882141
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- Macro F1: 0.7681095738330185
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- Micro F1: 0.8882102517882141
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- Weighted F1: 0.8873062298114072
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- Macro Precision: 0.8125021386404774
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- Micro Precision: 0.8882102517882141
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- Weighted Precision: 0.8875709606885154
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- Macro Recall: 0.7429489567097202
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- Micro Recall: 0.8882102517882141
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- Weighted Recall: 0.8882102517882141
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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/EXOP/autotrain-exop-msc-flat-categories-multilingual-1147942216
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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("EXOP/autotrain-exop-msc-flat-categories-multilingual-1147942216", use_auth_token=True)
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tokenizer = AutoTokenizer.from_pretrained("EXOP/autotrain-exop-msc-flat-categories-multilingual-1147942216", 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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"_num_labels": 142,
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"BertForSequenceClassification"
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
277 |
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|
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|
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|
280 |
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|
281 |
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|
282 |
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|
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|
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|
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|
286 |
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|
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|
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|
289 |
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|
290 |
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|
291 |
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|
292 |
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|
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|
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|
295 |
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|
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|
297 |
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|
298 |
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|
299 |
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|
300 |
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|
301 |
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"6000000": 141
|
302 |
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},
|
303 |
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|
304 |
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|
305 |
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|
306 |
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"model_type": "bert",
|
307 |
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|
308 |
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|
309 |
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|
310 |
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"padding": "max_length",
|
311 |
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|
312 |
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|
313 |
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"pooler_num_fc_layers": 3,
|
314 |
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"pooler_size_per_head": 128,
|
315 |
+
"pooler_type": "first_token_transform",
|
316 |
+
"position_embedding_type": "absolute",
|
317 |
+
"problem_type": "single_label_classification",
|
318 |
+
"torch_dtype": "float32",
|
319 |
+
"transformers_version": "4.20.0",
|
320 |
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"type_vocab_size": 2,
|
321 |
+
"use_cache": true,
|
322 |
+
"vocab_size": 105879
|
323 |
+
}
|
pytorch_model.bin
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
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2 |
+
oid sha256:1bee5c6fdccee72e394847ba2bb78afdb25c0f016f1e953f875fdf7be577816e
|
3 |
+
size 669933421
|
special_tokens_map.json
ADDED
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"cls_token": "[CLS]",
|
3 |
+
"mask_token": "[MASK]",
|
4 |
+
"pad_token": "[PAD]",
|
5 |
+
"sep_token": "[SEP]",
|
6 |
+
"unk_token": "[UNK]"
|
7 |
+
}
|
tokenizer.json
ADDED
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|
|
tokenizer_config.json
ADDED
@@ -0,0 +1,14 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"cls_token": "[CLS]",
|
3 |
+
"do_lower_case": true,
|
4 |
+
"mask_token": "[MASK]",
|
5 |
+
"model_max_length": 512,
|
6 |
+
"name_or_path": "AutoTrain",
|
7 |
+
"pad_token": "[PAD]",
|
8 |
+
"sep_token": "[SEP]",
|
9 |
+
"special_tokens_map_file": null,
|
10 |
+
"strip_accents": null,
|
11 |
+
"tokenize_chinese_chars": true,
|
12 |
+
"tokenizer_class": "BertTokenizer",
|
13 |
+
"unk_token": "[UNK]"
|
14 |
+
}
|
vocab.txt
ADDED
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|
|