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README.md

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+---
+language:
+- en
+base_model: FacebookAI/roberta-large
+tags:
+- generated_from_trainer
+datasets:
+- glue
+metrics:
+- accuracy
+- f1
+model-index:
+- name: QQP
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: GLUE QQP
+      type: glue
+      args: qqp
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9207024486767252
+    - name: F1
+      type: f1
+      value: 0.8944283456269757
+---
+
+<!-- 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. -->
+
+# QQP
+
+This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the GLUE QQP dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2704
+- Accuracy: 0.9207
+- F1: 0.8944
+- Combined Score: 0.9076
+
+## 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: 64
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 6.0
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Combined Score |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
+| 0.2392        | 1.0   | 5686  | 0.2472          | 0.9049   | 0.8685 | 0.8867         |
+| 0.1884        | 2.0   | 11372 | 0.2308          | 0.9089   | 0.8832 | 0.8960         |
+| 0.1351        | 3.0   | 17058 | 0.2317          | 0.9180   | 0.8894 | 0.9037         |
+| 0.1051        | 4.0   | 22744 | 0.2704          | 0.9207   | 0.8944 | 0.9076         |
+| 0.0794        | 5.0   | 28430 | 0.3272          | 0.9194   | 0.8911 | 0.9053         |
+| 0.0564        | 6.0   | 34116 | 0.3516          | 0.9207   | 0.8940 | 0.9073         |
+
+
+### Framework versions
+
+- Transformers 4.43.3
+- Pytorch 1.11.0+cu113
+- Datasets 2.20.0
+- Tokenizers 0.19.1

all_results.json

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+    "eval_f1": 0.8944283456269757,
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+    "train_runtime": 24723.4908,
+    "train_samples": 363846,
+    "train_samples_per_second": 88.3,
+    "train_steps_per_second": 1.38
+}

config.json

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+{
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+  "architectures": [
+    "RobertaForSequenceClassification"
+  ],
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+  "finetuning_task": "qqp",
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "label2id": {
+    "duplicate": 1,
+    "not_duplicate": 0
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+  "layer_norm_eps": 1e-05,
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+  "model_type": "roberta",
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+  "problem_type": "single_label_classification",
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+  "transformers_version": "4.43.3",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 50265
+}

eval_results.json

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+    "eval_steps_per_second": 31.114
+}

model.safetensors

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special_tokens_map.json

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tokenizer_config.json

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train_results.json

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