End of training

README.md

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+---
+license: mit
+base_model: openai-community/roberta-large-openai-detector
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- recall
+- precision
+- f1
+model-index:
+- name: openai-roberta-large-AI-detection
+  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. -->
+
+# openai-roberta-large-AI-detection
+
+This model is a fine-tuned version of [openai-community/roberta-large-openai-detector](https://huggingface.co/openai-community/roberta-large-openai-detector) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5761
+- Accuracy: 0.7308
+- Recall: 0.7513
+- Precision: 0.7595
+- F1: 0.7554
+
+## 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
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.6973        | 1.0   | 197  | 0.5936          | 0.7071   | 0.9652 | 0.6612    | 0.7848 |
+| 0.658         | 2.0   | 394  | 0.5761          | 0.7308   | 0.7513 | 0.7595    | 0.7554 |
+| 0.4746        | 3.0   | 591  | 0.6044          | 0.7071   | 0.8690 | 0.6857    | 0.7665 |
+| 0.3514        | 4.0   | 788  | 0.7278          | 0.7293   | 0.8636 | 0.7099    | 0.7793 |
+| 0.2263        | 5.0   | 985  | 1.2186          | 0.7071   | 0.8636 | 0.6872    | 0.7654 |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

config.json

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+{
+  "_name_or_path": "openai-community/roberta-large-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": 1024,
+  "id2label": {
+    "0": "AI",
+    "1": "human"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "roberta",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.38.2",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 50265
+}

logs/events.out.tfevents.1711557407.2f4024a4ed4b.598.0

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special_tokens_map.json

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+  "cls_token": "<s>",
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+  "mask_token": {
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+    "single_word": false
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+  "pad_token": "<pad>",
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+  "unk_token": "<unk>"
+}

tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
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+  "tokenizer_class": "RobertaTokenizer",
+  "trim_offsets": true,
+  "unk_token": "<unk>"
+}

training_args.bin

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