Initial model push after training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google-bert/bert-large-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: math_question_grade_detection_Bert_databalanced_v2
+  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. -->
+
+# math_question_grade_detection_Bert_databalanced_v2
+
+This model is a fine-tuned version of [google-bert/bert-large-uncased](https://huggingface.co/google-bert/bert-large-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5945
+- Accuracy: 0.8127
+- Precision: 0.8116
+- Recall: 0.8127
+- F1: 0.8110
+
+## 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: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 200
+- training_steps: 1000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| No log        | 0.2817 | 50   | 2.1406          | 0.1698   | 0.1183    | 0.1698 | 0.1327 |
+| No log        | 0.5634 | 100  | 1.8833          | 0.3540   | 0.3387    | 0.3540 | 0.2911 |
+| No log        | 0.8451 | 150  | 1.5465          | 0.4365   | 0.4580    | 0.4365 | 0.4060 |
+| No log        | 1.1268 | 200  | 1.2969          | 0.4937   | 0.4950    | 0.4937 | 0.4471 |
+| No log        | 1.4085 | 250  | 1.0146          | 0.6143   | 0.6253    | 0.6143 | 0.5906 |
+| No log        | 1.6901 | 300  | 0.8713          | 0.6778   | 0.6771    | 0.6778 | 0.6476 |
+| No log        | 1.9718 | 350  | 0.7740          | 0.7016   | 0.7000    | 0.7016 | 0.6896 |
+| No log        | 2.2535 | 400  | 0.7760          | 0.6968   | 0.7068    | 0.6968 | 0.6872 |
+| No log        | 2.5352 | 450  | 0.6579          | 0.7619   | 0.7726    | 0.7619 | 0.7590 |
+| 1.2792        | 2.8169 | 500  | 0.6872          | 0.7429   | 0.7571    | 0.7429 | 0.7418 |
+| 1.2792        | 3.0986 | 550  | 0.6073          | 0.7698   | 0.7783    | 0.7698 | 0.7700 |
+| 1.2792        | 3.3803 | 600  | 0.6297          | 0.7714   | 0.7840    | 0.7714 | 0.7718 |
+| 1.2792        | 3.6620 | 650  | 0.6160          | 0.7762   | 0.7764    | 0.7762 | 0.7731 |
+| 1.2792        | 3.9437 | 700  | 0.5895          | 0.8111   | 0.8147    | 0.8111 | 0.8110 |
+| 1.2792        | 4.2254 | 750  | 0.5717          | 0.8111   | 0.8087    | 0.8111 | 0.8089 |
+| 1.2792        | 4.5070 | 800  | 0.5767          | 0.8095   | 0.8126    | 0.8095 | 0.8083 |
+| 1.2792        | 4.7887 | 850  | 0.5898          | 0.8016   | 0.8029    | 0.8016 | 0.7995 |
+| 1.2792        | 5.0704 | 900  | 0.5908          | 0.8127   | 0.8143    | 0.8127 | 0.8115 |
+| 1.2792        | 5.3521 | 950  | 0.5972          | 0.8111   | 0.8136    | 0.8111 | 0.8102 |
+| 0.304         | 5.6338 | 1000 | 0.5945          | 0.8127   | 0.8116    | 0.8127 | 0.8110 |
+
+
+### Framework versions
+
+- Transformers 4.46.3
+- Pytorch 2.4.0
+- Datasets 3.1.0
+- Tokenizers 0.20.3

config.json

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+{
+  "_name_or_path": "google-bert/bert-large-uncased",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.46.3",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

model.safetensors

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runs/Dec18_07-51-46_8c41b66f7827/events.out.tfevents.1734508320.8c41b66f7827.23.0

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training_args.bin

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