Training in progress, epoch 1

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- glue
+metrics:
+- matthews_correlation
+model-index:
+- name: bert-base-cased
+ results:
+ - task:
+ name: Text Classification
+ type: text-classification
+ dataset:
+ name: glue
+ type: glue
+ config: cola
+ split: validation
+ args: cola
+ metrics:
+ - name: Matthews Correlation
+ type: matthews_correlation
+ value: 0.5845760203069087
+---
+
+<!-- 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-base-cased
+
+This model was trained from scratch on the glue dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7846
+- Matthews Correlation: 0.5846
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
+|:-------------:|:-----:|:----:|:---------------:|:--------------------:|
+| 0.437 | 1.0 | 1069 | 0.4197 | 0.5575 |
+| 0.3138 | 2.0 | 2138 | 0.6454 | 0.5804 |
+| 0.2068 | 3.0 | 3207 | 0.7846 | 0.5846 |
+
+
+### Framework versions
+
+- Transformers 4.33.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3

config.json

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+{
+ "_name_or_path": "bert-base-cased",
+ "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,
+ "initializer_range": 0.02,
+ "intermediate_size": 3072,
+ "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": "4.33.2",
+ "type_vocab_size": 2,
+ "use_cache": true,
+ "vocab_size": 28996
+}

pytorch_model.bin

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+size 433315633

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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+{
+ "clean_up_tokenization_spaces": true,
+ "cls_token": "[CLS]",
+ "do_lower_case": false,
+ "mask_token": "[MASK]",
+ "max_length": 512,
+ "model_max_length": 512,
+ "pad_token": "[PAD]",
+ "sep_token": "[SEP]",
+ "stride": 0,
+ "strip_accents": null,
+ "tokenize_chinese_chars": true,
+ "tokenizer_class": "BertTokenizer",
+ "truncation_side": "right",
+ "truncation_strategy": "longest_first",
+ "unk_token": "[UNK]"
+}

training_args.bin

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