Model save

README.md

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+---
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- ag_news
+metrics:
+- f1
+model-index:
+- name: ag-news-twitter-76800-bert-base-uncased
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: ag_news
+      type: ag_news
+      config: default
+      split: test
+      args: default
+    metrics:
+    - name: F1
+      type: f1
+      value: 0.9414991482921289
+---
+
+<!-- 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. -->
+
+# ag-news-twitter-76800-bert-base-uncased
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the ag_news dataset.
+It achieves the following results on the evaluation set:
+- F1: 0.9415
+- Acc: 0.9416
+- Loss: 0.5192
+
+## 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
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step  | F1     | Acc    | Validation Loss |
+|:-------------:|:-----:|:-----:|:------:|:------:|:---------------:|
+| 0.2328        | 1.0   | 4800  | 0.9289 | 0.9289 | 0.2082          |
+| 0.2061        | 2.0   | 9600  | 0.9366 | 0.9367 | 0.2154          |
+| 0.1488        | 3.0   | 14400 | 0.9401 | 0.9401 | 0.2181          |
+| 0.114         | 4.0   | 19200 | 0.9280 | 0.9275 | 0.3199          |
+| 0.0818        | 5.0   | 24000 | 0.9399 | 0.94   | 0.2953          |
+| 0.051         | 6.0   | 28800 | 0.9402 | 0.9403 | 0.3828          |
+| 0.0413        | 7.0   | 33600 | 0.9404 | 0.9403 | 0.4327          |
+| 0.0342        | 8.0   | 38400 | 0.9395 | 0.9395 | 0.4291          |
+| 0.0192        | 9.0   | 43200 | 0.9422 | 0.9422 | 0.4170          |
+| 0.0204        | 10.0  | 48000 | 0.9374 | 0.9374 | 0.4761          |
+| 0.0125        | 11.0  | 52800 | 0.9358 | 0.9359 | 0.5126          |
+| 0.0124        | 12.0  | 57600 | 0.9415 | 0.9416 | 0.5192          |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.1.0+cu121
+- Datasets 2.14.6
+- Tokenizers 0.14.1

config.json

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+{
+  "_name_or_path": "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": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2,
+    "LABEL_3": 3
+  },
+  "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": "4.35.0",
+  "type_vocab_size": 2,
+  "use_cache": false,
+  "vocab_size": 30522
+}

model.safetensors

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+oid sha256:f628f583ca43aa15b991bdc53aed442d10569d0588ef0b3da4fbc1f96a18d275
+size 437964800

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 4856