Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use fredymad/bert_Pfinal_2e-5_16_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fredymad/bert_Pfinal_2e-5_16_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fredymad/bert_Pfinal_2e-5_16_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fredymad/bert_Pfinal_2e-5_16_2") model = AutoModelForSequenceClassification.from_pretrained("fredymad/bert_Pfinal_2e-5_16_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files- config.json +4 -3
- pytorch_model.bin +2 -2
- runs/Jun02_10-04-14_93fdb2dd3a4d/1685700353.7147691/events.out.tfevents.1685700353.93fdb2dd3a4d.2801.1 +3 -0
- runs/Jun02_10-04-14_93fdb2dd3a4d/events.out.tfevents.1685700353.93fdb2dd3a4d.2801.0 +3 -0
- tokenizer.json +0 -0
- tokenizer_config.json +3 -1
- training_args.bin +1 -1
- vocab.txt +0 -0
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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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"
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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": "4.28.0",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size":
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}
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{
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"_name_or_path": "dccuchile/bert-base-spanish-wwm-uncased",
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"architectures": [
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"BertForSequenceClassification"
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],
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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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"output_past": true,
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"pad_token_id": 1,
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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": "4.28.0",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 31002
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}
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pytorch_model.bin
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oid sha256:99d871f8dad3ac69841c0a44c09713aa458137986cff1802be17cb0342b2d152
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size 439482485
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runs/Jun02_10-04-14_93fdb2dd3a4d/1685700353.7147691/events.out.tfevents.1685700353.93fdb2dd3a4d.2801.1
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oid sha256:31d848272c8dbe65aed3dfc4506ac0251f087a3ebdc2fd7c0d1050c8c749d69d
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size 5885
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runs/Jun02_10-04-14_93fdb2dd3a4d/events.out.tfevents.1685700353.93fdb2dd3a4d.2801.0
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oid sha256:536e96a48c1f6758a2040fa8c817f547044d09785629e51e72e4bd7a5c979c4d
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size 4615
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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":
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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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"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": 512,
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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": false,
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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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training_args.bin
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version https://git-lfs.github.com/spec/v1
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size 3579
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version https://git-lfs.github.com/spec/v1
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oid sha256:9333d63c2be7fd24ac8e8623a701528f941569e4fa9ee9f39e357f9c344f4734
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size 3579
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vocab.txt
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