Training in progress epoch 0
Browse files- README.md +54 -0
- config.json +76 -0
- special_tokens_map.json +7 -0
- tf_model.h5 +3 -0
- tokenizer.json +0 -0
- tokenizer_config.json +13 -0
- vocab.txt +0 -0
README.md
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---
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base_model: bert-base-chinese
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tags:
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- generated_from_keras_callback
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model-index:
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- name: AIYIYA/my_wr1
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results: []
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---
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<!-- This model card has been generated automatically according to the information Keras had access to. You should
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probably proofread and complete it, then remove this comment. -->
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# AIYIYA/my_wr1
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This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert-base-chinese) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Train Loss: 2.9423
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- Validation Loss: 2.5705
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- Train Accuracy: 0.1842
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- Epoch: 0
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 30, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
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- training_precision: float32
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### Training results
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| Train Loss | Validation Loss | Train Accuracy | Epoch |
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|:----------:|:---------------:|:--------------:|:-----:|
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| 2.9423 | 2.5705 | 0.1842 | 0 |
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### Framework versions
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- Transformers 4.31.0
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- TensorFlow 2.12.0
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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config.json
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{
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"_name_or_path": "bert-base-chinese",
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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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"directionality": "bidi",
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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": "\u5176\u4ed6",
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"1": "\u59d3\u540d",
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"2": "\u8eab\u4efd\u8bc1\u53f7",
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"3": "\u624b\u673a\u53f7",
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"4": "\u5730\u5740",
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"5": "\u90ae\u7bb1",
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"6": "QQ",
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"7": "\u82f1\u6587\u59d3",
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"8": "\u516c\u53f8\u540d\u79f0",
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"9": "\u8054\u7cfb\u4eba\u59d3\u540d",
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"10": "\u7edf\u4e00\u793e\u4f1a\u4fe1\u7528\u4ee3\u7801",
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"11": "\u90ae\u7f16",
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"12": "\u5b57\u6bcd",
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"13": "\u6c49\u5b57",
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"14": "\u786e\u8ba4\u5bc6\u7801",
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"15": "\u7528\u6237\u540d",
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"16": "\u5bc6\u7801",
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"17": "\u524d\u7aef\u9a8c\u8bc1\u7801",
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"18": "\u52a8\u6001\u9a8c\u8bc1\u7801",
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"19": "\u4f20\u771f",
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"20": "\u6635\u79f0"
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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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"QQ": 6,
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"\u4f20\u771f": 19,
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"\u516c\u53f8\u540d\u79f0": 8,
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"\u5176\u4ed6": 0,
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"\u524d\u7aef\u9a8c\u8bc1\u7801": 17,
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"\u52a8\u6001\u9a8c\u8bc1\u7801": 18,
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"\u5730\u5740": 4,
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"\u59d3\u540d": 1,
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"\u5b57\u6bcd": 12,
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"\u5bc6\u7801": 16,
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"\u624b\u673a\u53f7": 3,
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"\u6635\u79f0": 20,
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"\u6c49\u5b57": 13,
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"\u7528\u6237\u540d": 15,
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"\u786e\u8ba4\u5bc6\u7801": 14,
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"\u7edf\u4e00\u793e\u4f1a\u4fe1\u7528\u4ee3\u7801": 10,
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"\u8054\u7cfb\u4eba\u59d3\u540d": 9,
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"\u82f1\u6587\u59d3": 7,
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"\u8eab\u4efd\u8bc1\u53f7": 2,
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"\u90ae\u7bb1": 5,
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"\u90ae\u7f16": 11
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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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"pooler_fc_size": 768,
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"pooler_num_attention_heads": 12,
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"pooler_num_fc_layers": 3,
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"pooler_size_per_head": 128,
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"pooler_type": "first_token_transform",
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"position_embedding_type": "absolute",
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"transformers_version": "4.31.0",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 21128
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}
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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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tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:d69301950701e734a86070603fe8933538fe10b68e04c669cfb7fd4872ec8f5b
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size 409423204
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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": false,
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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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vocab.txt
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