MaryDatascientist/B_model2

README.md

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+---
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: B_model2
+  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. -->
+
+# B_model2
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0339
+- Precision: 0.9316
+- Recall: 0.9369
+- F1: 0.9342
+- Accuracy: 0.9883
+
+## 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: 2.65095847146542e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.057         | 0.03  | 500   | 0.0598          | 0.8641    | 0.8859 | 0.8749 | 0.9795   |
+| 0.0512        | 0.06  | 1000  | 0.0496          | 0.9001    | 0.8916 | 0.8958 | 0.9827   |
+| 0.0356        | 0.09  | 1500  | 0.0512          | 0.8670    | 0.9215 | 0.8934 | 0.9823   |
+| 0.051         | 0.12  | 2000  | 0.0549          | 0.8399    | 0.9425 | 0.8883 | 0.9808   |
+| 0.0485        | 0.15  | 2500  | 0.0459          | 0.8909    | 0.9284 | 0.9093 | 0.9843   |
+| 0.0411        | 0.18  | 3000  | 0.0449          | 0.9071    | 0.9137 | 0.9104 | 0.9844   |
+| 0.0376        | 0.21  | 3500  | 0.0428          | 0.9085    | 0.9138 | 0.9111 | 0.9851   |
+| 0.0408        | 0.24  | 4000  | 0.0419          | 0.9136    | 0.9146 | 0.9141 | 0.9850   |
+| 0.0501        | 0.27  | 4500  | 0.0406          | 0.9221    | 0.9089 | 0.9154 | 0.9855   |
+| 0.0386        | 0.3   | 5000  | 0.0390          | 0.9214    | 0.9166 | 0.9190 | 0.9863   |
+| 0.0372        | 0.34  | 5500  | 0.0390          | 0.9027    | 0.9398 | 0.9209 | 0.9860   |
+| 0.0353        | 0.37  | 6000  | 0.0384          | 0.9195    | 0.9261 | 0.9228 | 0.9865   |
+| 0.0353        | 0.4   | 6500  | 0.0375          | 0.9257    | 0.9216 | 0.9236 | 0.9866   |
+| 0.0455        | 0.43  | 7000  | 0.0383          | 0.9186    | 0.9265 | 0.9225 | 0.9865   |
+| 0.025         | 0.46  | 7500  | 0.0391          | 0.9093    | 0.9378 | 0.9233 | 0.9865   |
+| 0.0328        | 0.49  | 8000  | 0.0380          | 0.9320    | 0.9179 | 0.9249 | 0.9869   |
+| 0.0298        | 0.52  | 8500  | 0.0384          | 0.9222    | 0.9287 | 0.9254 | 0.9869   |
+| 0.0337        | 0.55  | 9000  | 0.0372          | 0.9260    | 0.9208 | 0.9234 | 0.9867   |
+| 0.0203        | 0.58  | 9500  | 0.0400          | 0.9166    | 0.9343 | 0.9254 | 0.9868   |
+| 0.0312        | 0.61  | 10000 | 0.0364          | 0.9178    | 0.9361 | 0.9269 | 0.9870   |
+| 0.0332        | 0.64  | 10500 | 0.0359          | 0.9196    | 0.9356 | 0.9275 | 0.9872   |
+| 0.0291        | 0.67  | 11000 | 0.0363          | 0.9291    | 0.9253 | 0.9272 | 0.9871   |
+| 0.0289        | 0.7   | 11500 | 0.0355          | 0.9304    | 0.9317 | 0.9310 | 0.9877   |
+| 0.0196        | 0.73  | 12000 | 0.0359          | 0.9251    | 0.9357 | 0.9304 | 0.9875   |
+| 0.0251        | 0.76  | 12500 | 0.0357          | 0.9187    | 0.9420 | 0.9302 | 0.9875   |
+| 0.0235        | 0.79  | 13000 | 0.0357          | 0.9249    | 0.9408 | 0.9328 | 0.9879   |
+| 0.0275        | 0.82  | 13500 | 0.0353          | 0.9308    | 0.9345 | 0.9326 | 0.9879   |
+| 0.0269        | 0.85  | 14000 | 0.0352          | 0.9300    | 0.9328 | 0.9314 | 0.9880   |
+| 0.0251        | 0.88  | 14500 | 0.0348          | 0.9375    | 0.9316 | 0.9346 | 0.9884   |
+| 0.0143        | 0.91  | 15000 | 0.0347          | 0.9275    | 0.9408 | 0.9341 | 0.9882   |
+| 0.0187        | 0.94  | 15500 | 0.0342          | 0.9299    | 0.9373 | 0.9336 | 0.9882   |
+| 0.0209        | 0.98  | 16000 | 0.0339          | 0.9316    | 0.9369 | 0.9342 | 0.9883   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0

config.json

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+{
+  "_name_or_path": "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": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3",
+    "4": "LABEL_4",
+    "5": "LABEL_5",
+    "6": "LABEL_6",
+    "7": "LABEL_7",
+    "8": "LABEL_8",
+    "9": "LABEL_9",
+    "10": "LABEL_10"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_10": 10,
+    "LABEL_2": 2,
+    "LABEL_3": 3,
+    "LABEL_4": 4,
+    "LABEL_5": 5,
+    "LABEL_6": 6,
+    "LABEL_7": 7,
+    "LABEL_8": 8,
+    "LABEL_9": 9
+  },
+  "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": "4.35.2",
+  "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 sha256:5697c2dc8f7175248c5a2339ebcd388fe3e7abd3da6af44aa389ea772da6288b
+size 435623772

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 4536