End of training
Browse files- README.md +61 -0
- config.json +46 -0
- model.safetensors +3 -0
- runs/Apr17_22-09-26_ml/events.out.tfevents.1713362966.ml.525063.0 +3 -0
- training_args.bin +3 -0
README.md
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---
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base_model: google-bert/bert-base-chinese
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: checkpoint
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# checkpoint
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This model is a fine-tuned version of [google-bert/bert-base-chinese](https://huggingface.co/google-bert/bert-base-chinese) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0231
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- Accuracy: 0.9973
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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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- learning_rate: 5e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 3.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 214 | 0.1003 | 0.9850 |
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| No log | 2.0 | 428 | 0.0372 | 0.9959 |
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| 0.0581 | 3.0 | 642 | 0.0231 | 0.9973 |
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### Framework versions
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- Transformers 4.37.2
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- Pytorch 2.1.2
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- Datasets 2.18.0
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- Tokenizers 0.15.1
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config.json
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{
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"_name_or_path": "google-bert/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": "LABEL_0",
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"1": "LABEL_1",
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"2": "LABEL_2",
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"3": "LABEL_3",
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"4": "LABEL_4"
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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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"LABEL_0": 0,
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"LABEL_1": 1,
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"LABEL_2": 2,
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"LABEL_3": 3,
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"LABEL_4": 4
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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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"problem_type": "single_label_classification",
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"torch_dtype": "float32",
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"transformers_version": "4.37.2",
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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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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:217a90eb7a75e1761ae8eb30740b98176c83a3a2540e3fed8aa0585f73d55324
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size 409109468
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runs/Apr17_22-09-26_ml/events.out.tfevents.1713362966.ml.525063.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:2fccef42a806e901675751bfe12f39241738212f221e8250c94a0b0b1c408d6a
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size 6200
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:9526ce72fd7157ed5c2fe4ba1b64ba2b4a5c7600878715b96f3b338f63c5508b
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size 4664
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