Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use jayavibhav/bert-classification-5ksamples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jayavibhav/bert-classification-5ksamples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jayavibhav/bert-classification-5ksamples")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jayavibhav/bert-classification-5ksamples") model = AutoModelForSequenceClassification.from_pretrained("jayavibhav/bert-classification-5ksamples") - Notebooks
- Google Colab
- Kaggle
Commit ·
26a8ae3
1
Parent(s): 3decdff
Training in progress, epoch 1
Browse files- .gitignore +1 -0
- config.json +35 -0
- pytorch_model.bin +3 -0
- runs/Aug09_07-30-50_77073d7374c6/events.out.tfevents.1691566261.77073d7374c6.28.0 +3 -0
- special_tokens_map.json +7 -0
- tokenizer.json +0 -0
- tokenizer_config.json +13 -0
- training_args.bin +3 -0
- vocab.txt +0 -0
.gitignore
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checkpoint-*/
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config.json
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{
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"_name_or_path": "bert-base-uncased",
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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": 768,
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"id2label": {
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"0": "POSITIVE",
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"1": "NEGATIVE"
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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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"NEGATIVE": 1,
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"POSITIVE": 0
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},
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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": 12,
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"num_hidden_layers": 12,
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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": "4.30.2",
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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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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:41453f3e38a2fedcb69cdbea06b49f7e3b8d304f48468d9c5e9484c6d904ff96
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size 438007925
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runs/Aug09_07-30-50_77073d7374c6/events.out.tfevents.1691566261.77073d7374c6.28.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:666b681645926e5400fe6166a69bc39d2bcf6c93daee4cadfc534405a10e8dd1
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size 4501
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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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"clean_up_tokenization_spaces": true,
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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": 512,
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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 sha256:6af337fcb0877f3e9d093096079df3d4a679bef6d92e07355a2c20f6b8331551
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size 3963
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vocab.txt
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