End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google-bert/bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: intent_classfication
+  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. -->
+
+# intent_classfication
+
+This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1313
+- Accuracy: 0.9622
+
+## 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: 16
+- seed: 42
+- 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
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.647         | 1.0   | 655  | 1.0548          | 0.8502   |
+| 1.0688        | 2.0   | 1310 | 0.5307          | 0.8945   |
+| 0.683         | 3.0   | 1965 | 0.3331          | 0.9255   |
+| 0.3873        | 4.0   | 2620 | 0.2548          | 0.9396   |
+| 0.326         | 5.0   | 3275 | 0.2134          | 0.9480   |
+| 0.29          | 6.0   | 3930 | 0.1842          | 0.9538   |
+| 0.2409        | 7.0   | 4585 | 0.1675          | 0.9553   |
+| 0.2292        | 8.0   | 5240 | 0.1594          | 0.9576   |
+| 0.2217        | 9.0   | 5895 | 0.1492          | 0.9595   |
+| 0.2029        | 10.0  | 6550 | 0.1433          | 0.9595   |
+| 0.2036        | 11.0  | 7205 | 0.1369          | 0.9614   |
+| 0.1865        | 12.0  | 7860 | 0.1347          | 0.9614   |
+| 0.1899        | 13.0  | 8515 | 0.1327          | 0.9622   |
+| 0.182         | 14.0  | 9170 | 0.1315          | 0.9622   |
+| 0.181         | 15.0  | 9825 | 0.1313          | 0.9622   |
+
+
+### Framework versions
+
+- Transformers 4.47.0
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0

config.json

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+{
+  "_name_or_path": "google-bert/bert-base-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": 768,
+  "id2label": {
+    "0": "AddToPlaylist",
+    "1": "BookRestaurant",
+    "2": "GetWeather",
+    "3": "PlayMusic",
+    "4": "RateBook",
+    "5": "SearchCreativeWork",
+    "6": "SearchScreeningEvent"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "AddToPlaylist": 0,
+    "BookRestaurant": 1,
+    "GetWeather": 2,
+    "PlayMusic": 3,
+    "RateBook": 4,
+    "SearchCreativeWork": 5,
+    "SearchScreeningEvent": 6
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.47.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

model.safetensors

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+size 437974028

runs/Feb10_08-52-25_07c0084a7fca/events.out.tfevents.1739177546.07c0084a7fca.31.0

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special_tokens_map.json

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+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "extra_special_tokens": {},
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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