End of training

README.md

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+---
+license: apache-2.0
+base_model: google/bigbird-roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: bigbird-roberta-base-finetuned-sql-classification-with_schema_question
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# bigbird-roberta-base-finetuned-sql-classification-with_schema_question
+
+This model is a fine-tuned version of [google/bigbird-roberta-base](https://huggingface.co/google/bigbird-roberta-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4232
+- Accuracy: 0.8337
+- F1: 0.8617
+- Precision: 0.7971
+- Recall: 0.9375
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.6156        | 1.0   | 1290 | 0.4973          | 0.7767   | 0.8292 | 0.7180    | 0.9811 |
+| 0.4798        | 2.0   | 2580 | 0.4877          | 0.7860   | 0.8358 | 0.7253    | 0.9860 |
+| 0.4841        | 3.0   | 3870 | 0.4767          | 0.7969   | 0.8400 | 0.7434    | 0.9656 |
+| 0.4573        | 4.0   | 5160 | 0.4716          | 0.8225   | 0.8513 | 0.7921    | 0.92   |
+| 0.4048        | 5.0   | 6450 | 0.4232          | 0.8337   | 0.8617 | 0.7971    | 0.9375 |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.2.0+cu121
+- Datasets 2.17.0
+- Tokenizers 0.15.2

config.json

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+  "architectures": [
+    "BigBirdForSequenceClassification"
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+  "attention_probs_dropout_prob": 0.1,
+  "attention_type": "block_sparse",
+  "block_size": 64,
+  "bos_token_id": 1,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu_new",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "negative",
+    "1": "positive"
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+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
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+    "positive": 1
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+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 4096,
+  "model_type": "big_bird",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "num_random_blocks": 3,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "rescale_embeddings": false,
+  "sep_token_id": 66,
+  "torch_dtype": "float32",
+  "transformers_version": "4.37.2",
+  "type_vocab_size": 2,
+  "use_bias": true,
+  "use_cache": true,
+  "vocab_size": 50358
+}

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special_tokens_map.json

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tokenizer_config.json

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