End of training

README.md

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+---
+license: mit
+base_model: roberta-base-openai-detector
+tags:
+- generated_from_trainer
+datasets:
+- au_tex_tification
+metrics:
+- accuracy
+model-index:
+- name: roberta-base-openai-detector-autextification
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: au_tex_tification
+      type: au_tex_tification
+      config: detection_en
+      split: train
+      args: detection_en
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.55
+---
+
+<!-- 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. -->
+
+# roberta-base-openai-detector-autextification
+
+This model is a fine-tuned version of [roberta-base-openai-detector](https://huggingface.co/roberta-base-openai-detector) on the au_tex_tification dataset.
+It achieves the following results on the evaluation set:
+- Loss: 3.5239
+- Accuracy: 0.55
+- Roc Auc: 0.5000
+
+## 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: 5e-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 | Accuracy | Roc Auc |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------:|
+| 0.0003        | 1.0   | 10   | 2.8320          | 0.6      | 0.4896  |
+| 0.0002        | 2.0   | 20   | 3.2171          | 0.55     | 0.5     |
+| 0.0016        | 3.0   | 30   | 3.5239          | 0.55     | 0.5000  |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.0.0
+- Datasets 2.1.0
+- Tokenizers 0.14.1

config.json

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+{
+  "_name_or_path": "roberta-base-openai-detector",
+  "architectures": [
+    "RobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "Fake",
+    "1": "Real"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "Fake": 0,
+    "Real": 1
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.35.0",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 50265
+}

model.safetensors

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+size 498612824

training_args.bin

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