End of training

README.md

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+---
+license: apache-2.0
+base_model: google-bert/bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: 20240320102435_big_hinton
+  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. -->
+
+# 20240320102435_big_hinton
+
+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: 0.0351
+- Precision: 0.9436
+- Recall: 0.9308
+- F1: 0.9372
+- Accuracy: 0.9859
+
+## 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: 0.001
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 69
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 256
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 350
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0805        | 0.09  | 300  | 0.0626          | 0.9020    | 0.8843 | 0.8931 | 0.9758   |
+| 0.0969        | 0.18  | 600  | 0.0770          | 0.8912    | 0.8486 | 0.8694 | 0.9704   |
+| 0.0879        | 0.27  | 900  | 0.0682          | 0.8943    | 0.8733 | 0.8837 | 0.9735   |
+| 0.0778        | 0.36  | 1200 | 0.0612          | 0.9013    | 0.8891 | 0.8952 | 0.9762   |
+| 0.0703        | 0.44  | 1500 | 0.0564          | 0.9137    | 0.8909 | 0.9021 | 0.9779   |
+| 0.0638        | 0.53  | 1800 | 0.0521          | 0.9244    | 0.8975 | 0.9107 | 0.9799   |
+| 0.0579        | 0.62  | 2100 | 0.0480          | 0.9309    | 0.9029 | 0.9167 | 0.9812   |
+| 0.0534        | 0.71  | 2400 | 0.0447          | 0.9323    | 0.9095 | 0.9208 | 0.9825   |
+| 0.049         | 0.8   | 2700 | 0.0399          | 0.9329    | 0.9236 | 0.9282 | 0.9841   |
+| 0.0451        | 0.89  | 3000 | 0.0373          | 0.9411    | 0.9226 | 0.9318 | 0.9849   |
+| 0.0424        | 0.98  | 3300 | 0.0351          | 0.9436    | 0.9308 | 0.9372 | 0.9859   |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.0a0+6a974be
+- Datasets 2.18.0
+- Tokenizers 0.15.2

config.json

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+{
+  "_name_or_path": "google-bert/bert-base-uncased",
+  "architectures": [
+    "BertForTokenClassification"
+  ],
+  "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": "not inserted",
+    "1": "inserted"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "inserted": 1,
+    "not inserted": 0
+  },
+  "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",
+  "torch_dtype": "float32",
+  "transformers_version": "4.38.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f01dee14cd7aa52d9ed78de6db27a1378071a87eaa203a6c2e70f9948321251f
+size 435596088

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": true,
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "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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+size 4984