End of training
Browse files- README.md +64 -0
- config.json +35 -0
- model.safetensors +3 -0
- special_tokens_map.json +7 -0
- tokenizer.json +0 -0
- tokenizer_config.json +55 -0
- training_args.bin +3 -0
- vocab.txt +0 -0
    	
        README.md
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            ---
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            license: apache-2.0
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            base_model: bert-base-uncased
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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: bert-base-uncased-finetuned-sql-classification-with_schema_question
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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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            # bert-base-uncased-finetuned-sql-classification-with_schema_question
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            This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
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            It achieves the following results on the evaluation set:
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            - Loss: 0.3313
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            - Accuracy: 0.9277
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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: 4
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            - eval_batch_size: 4
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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: 5
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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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            | 0.6358        | 1.0   | 1036 | 0.5458          | 0.7165   |
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            | 0.4936        | 2.0   | 2072 | 0.4113          | 0.8881   |
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            | 0.4004        | 3.0   | 3108 | 0.4240          | 0.9026   |
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            | 0.3073        | 4.0   | 4144 | 0.3577          | 0.9122   |
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            | 0.2538        | 5.0   | 5180 | 0.3313          | 0.9277   |
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            ### Framework versions
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            - Transformers 4.37.2
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            - Pytorch 2.2.0+cu121
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            - Datasets 2.17.0
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            - Tokenizers 0.15.2
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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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              "initializer_range": 0.02,
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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_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": "4.37.2",
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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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        model.safetensors
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        special_tokens_map.json
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            {
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        tokenizer_config.json
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