Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use abigailp/vacc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abigailp/vacc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="abigailp/vacc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("abigailp/vacc") model = AutoModelForSequenceClassification.from_pretrained("abigailp/vacc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files- config.json +5 -6
- pytorch_model.bin +2 -2
- runs/Feb05_09-19-06_39aff3525dbc/1675588845.3018982/events.out.tfevents.1675588845.39aff3525dbc.108.1 +3 -0
- runs/Feb05_09-19-06_39aff3525dbc/events.out.tfevents.1675588845.39aff3525dbc.108.0 +3 -0
- tokenizer.json +1 -6
- tokenizer_config.json +4 -2
- training_args.bin +1 -1
config.json
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{
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"_name_or_path": "bert-
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"architectures": [
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"BertForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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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":
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"initializer_range": 0.02,
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"intermediate_size":
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads":
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"num_hidden_layers":
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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{
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"_name_or_path": "prajjwal1/bert-tiny",
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"architectures": [
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"BertForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 128,
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"initializer_range": 0.02,
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"intermediate_size": 512,
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 2,
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"num_hidden_layers": 2,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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pytorch_model.bin
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size
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version https://git-lfs.github.com/spec/v1
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size 17562607
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runs/Feb05_09-19-06_39aff3525dbc/1675588845.3018982/events.out.tfevents.1675588845.39aff3525dbc.108.1
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version https://git-lfs.github.com/spec/v1
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oid sha256:e495383dc8c144f01e60501676ca68a4aed316d0a2ee4ed67c2eed00652c8571
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size 5622
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runs/Feb05_09-19-06_39aff3525dbc/events.out.tfevents.1675588845.39aff3525dbc.108.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:911ce79b52abba8770e2315c23581d3ce486bc4057a127212c8f2de9ef3a6950
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size 40
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tokenizer.json
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{
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"version": "1.0",
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"truncation":
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"direction": "Right",
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"max_length": 512,
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"strategy": "LongestFirst",
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"stride": 0
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},
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"padding": {
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"strategy": "BatchLongest",
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"direction": "Right",
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{
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"version": "1.0",
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"truncation": null,
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"padding": {
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"strategy": "BatchLongest",
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"direction": "Right",
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tokenizer_config.json
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{
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"cls_token": "[CLS]",
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"do_lower_case": true,
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"mask_token": "[MASK]",
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"model_max_length":
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"name_or_path": "bert-
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"special_tokens_map_file": null,
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{
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"cls_token": "[CLS]",
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"do_basic_tokenize": true,
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"do_lower_case": true,
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"mask_token": "[MASK]",
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+
"model_max_length": 1000000000000000019884624838656,
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"name_or_path": "prajjwal1/bert-tiny",
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"never_split": null,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"special_tokens_map_file": null,
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 3451
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version https://git-lfs.github.com/spec/v1
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oid sha256:bfca74c3ab5251cbb4b5b78e47c9d7421fd05e88e5bd52ac62172f3b9a22075f
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size 3451
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