Model save

README.md

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+---
+license: apache-2.0
+base_model: bert-large-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: BERT_pretraining_h_100_wo_deepspeed
+  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. -->
+
+# BERT_pretraining_h_100_wo_deepspeed
+
+This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 5.7886
+- Accuracy: 0.1537
+
+## 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: 1e-05
+- train_batch_size: 208
+- eval_batch_size: 208
+- seed: 10
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 100000
+- num_epochs: 100
+
+### Training results
+
+| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
+|:-------------:|:-----:|:------:|:---------------:|:--------:|
+| 6.8769        | 0.36  | 10000  | 6.7582          | 0.1101   |
+| 6.4647        | 0.71  | 20000  | 6.4764          | 0.1314   |
+| 6.3679        | 1.07  | 30000  | 6.3218          | 0.1407   |
+| 6.252         | 1.42  | 40000  | 6.2139          | 0.1454   |
+| 6.2132        | 1.78  | 50000  | 6.1398          | 0.1478   |
+| 6.0407        | 2.13  | 60000  | 6.0774          | 0.1502   |
+| 6.0694        | 2.49  | 70000  | 6.0303          | 0.1516   |
+| 5.9996        | 2.84  | 80000  | 5.9893          | 0.1521   |
+| 5.9166        | 3.2   | 90000  | 5.9553          | 0.1526   |
+| 5.8915        | 3.55  | 100000 | 5.9261          | 0.1530   |
+| 5.8924        | 3.91  | 110000 | 5.8996          | 0.1534   |
+| 5.8972        | 4.26  | 120000 | 5.8814          | 0.1533   |
+| 5.8454        | 4.62  | 130000 | 5.8626          | 0.1532   |
+| 5.8104        | 4.97  | 140000 | 5.8494          | 0.1534   |
+| 5.8461        | 5.33  | 150000 | 5.8378          | 0.1534   |
+| 5.8476        | 5.68  | 160000 | 5.8246          | 0.1536   |
+| 5.7255        | 6.04  | 170000 | 5.8155          | 0.1532   |
+| 5.8431        | 6.39  | 180000 | 5.8068          | 0.1537   |
+| 5.7526        | 6.75  | 190000 | 5.7981          | 0.1537   |
+| 5.7826        | 7.1   | 200000 | 5.7886          | 0.1537   |
+
+
+### Framework versions
+
+- Transformers 4.37.1
+- Pytorch 2.1.2+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.1

config.json

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+{
+  "_name_or_path": "bert-large-uncased",
+  "architectures": [
+    "BertForMaskedLM"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "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",
+  "torch_dtype": "float32",
+  "transformers_version": "4.37.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "pad_token_id": 0,
+  "transformers_version": "4.37.1"
+}

logs/events.out.tfevents.1707750327.ki-g0009

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model.safetensors

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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
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+    "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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