Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Zainab984/BP-test1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Zainab984/BP-test1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Zainab984/BP-test1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Zainab984/BP-test1") model = AutoModelForSequenceClassification.from_pretrained("Zainab984/BP-test1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 500
Browse files- config.json +26 -0
- events.out.tfevents.1701065469.eaeab5e7c16b.616.0 +3 -0
- model.safetensors +3 -0
- runs/Nov27_06-11-09_eaeab5e7c16b/events.out.tfevents.1701065476.eaeab5e7c16b.616.1 +3 -0
- runs/Nov27_06-11-09_eaeab5e7c16b/events.out.tfevents.1701065476.eaeab5e7c16b.616.2 +3 -0
- special_tokens_map.json +7 -0
- tokenizer.json +0 -0
- tokenizer_config.json +57 -0
- training_args.bin +3 -0
- vocab.txt +0 -0
config.json
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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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"torch_dtype": "float32",
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"transformers_version": "4.35.2",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 30522
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}
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events.out.tfevents.1701065469.eaeab5e7c16b.616.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:d17f26eab33c36a543e8f3a7b3788613fb08c526b8b8ae323ea1eb4a3ac9e9c6
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size 88
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:34f0b17048a8deb82a3e834faf948f6f98115d36d06df3e121242a5efb7522c4
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size 17549312
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runs/Nov27_06-11-09_eaeab5e7c16b/events.out.tfevents.1701065476.eaeab5e7c16b.616.1
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version https://git-lfs.github.com/spec/v1
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oid sha256:af2e86fcf36f96141eecd4a7e25a66e235234cb84bcc6847d26c7810fe58c7e2
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size 7471
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runs/Nov27_06-11-09_eaeab5e7c16b/events.out.tfevents.1701065476.eaeab5e7c16b.616.2
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version https://git-lfs.github.com/spec/v1
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oid sha256:9b0de76f065598951be4097813b9297096f95e7a8ad1e3f74b56a6b12d249f2b
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size 7471
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special_tokens_map.json
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{
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"cls_token": "[CLS]",
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"mask_token": "[MASK]",
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"unk_token": "[UNK]"
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}
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tokenizer.json
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tokenizer_config.json
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{
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"added_tokens_decoder": {
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"0": {
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"content": "[PAD]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"100": {
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"content": "[UNK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"101": {
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"content": "[CLS]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"102": {
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"content": "[SEP]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"103": {
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"content": "[MASK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"clean_up_tokenization_spaces": true,
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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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"never_split": null,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "BertTokenizer",
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"unk_token": "[UNK]"
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}
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:92dbfd54308c807d46feeb8ebd45810d55369031e045b5516abde3f617b38d6a
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size 4536
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vocab.txt
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