commit from ssssss

README的副本.md

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+---
+language:
+- en
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- glue
+metrics:
+- accuracy
+- f1
+model-index:
+- name: bert-base-uncased-finetuning
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: GLUE MRPC
+      type: glue
+      args: mrpc
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8161764705882353
+    - name: F1
+      type: f1
+      value: 0.8739495798319329
+---
+
+<!-- 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-uncased-finetuning
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the GLUE MRPC dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4063
+- Accuracy: 0.8162
+- F1: 0.8739
+- Combined Score: 0.8451
+
+## 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: 1.0
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.24.0
+- Pytorch 1.13.1
+- Datasets 2.10.1
+- Tokenizers 0.11.0

all_results.json

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+{
+    "epoch": 1.0,
+    "eval_accuracy": 0.8161764705882353,
+    "eval_combined_score": 0.8450630252100841,
+    "eval_f1": 0.8739495798319329,
+    "eval_loss": 0.40634819865226746,
+    "eval_runtime": 69.3579,
+    "eval_samples": 408,
+    "eval_samples_per_second": 5.883,
+    "eval_steps_per_second": 0.735,
+    "train_loss": 0.532436129833878,
+    "train_runtime": 1869.0143,
+    "train_samples": 3668,
+    "train_samples_per_second": 1.963,
+    "train_steps_per_second": 0.246
+}

config.json

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+{
+  "_name_or_path": "bert-base-uncased",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "finetuning_task": "mrpc",
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "not_equivalent",
+    "1": "equivalent"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "equivalent": 1,
+    "not_equivalent": 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",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.24.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

eval_results.json

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+{
+    "epoch": 1.0,
+    "eval_accuracy": 0.8161764705882353,
+    "eval_combined_score": 0.8450630252100841,
+    "eval_f1": 0.8739495798319329,
+    "eval_loss": 0.40634819865226746,
+    "eval_runtime": 69.3579,
+    "eval_samples": 408,
+    "eval_samples_per_second": 5.883,
+    "eval_steps_per_second": 0.735
+}

pytorch_model.bin

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+size 438005109

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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+{
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "name_or_path": "bert-base-uncased",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "special_tokens_map_file": null,
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

train_results.json

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+{
+    "epoch": 1.0,
+    "train_loss": 0.532436129833878,
+    "train_runtime": 1869.0143,
+    "train_samples": 3668,
+    "train_samples_per_second": 1.963,
+    "train_steps_per_second": 0.246
+}

trainer_state.json

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+{
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 1.0,
+  "global_step": 459,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 1.0,
+      "step": 459,
+      "total_flos": 241272837765120.0,
+      "train_loss": 0.532436129833878,
+      "train_runtime": 1869.0143,
+      "train_samples_per_second": 1.963,
+      "train_steps_per_second": 0.246
+    }
+  ],
+  "max_steps": 459,
+  "num_train_epochs": 1,
+  "total_flos": 241272837765120.0,
+  "trial_name": null,
+  "trial_params": null
+}

training_args.bin

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