Model save

README.md

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+---
+library_name: transformers
+license: mit
+base_model: roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: roberta-base-pan-clef-subtask2
+  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. -->
+
+# roberta-base-pan-clef-subtask2
+
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 3.4936
+- Micro F1: 0.5654
+- Macro F1: 0.6413
+- Macro Recall: 0.7827
+- Accuracy: 0.5654
+
+## 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: 3e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 64
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 2
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Micro F1 | Macro F1 | Macro Recall | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:------------:|:--------:|
+| 0.1032        | 1.0    | 4515 | 3.0365          | 0.5613   | 0.6005   | 0.7793       | 0.5613   |
+| 0.0501        | 1.9997 | 9028 | 3.4936          | 0.5654   | 0.6413   | 0.7827       | 0.5654   |
+
+
+### Framework versions
+
+- Transformers 4.51.3
+- Pytorch 2.7.0+cu126
+- Datasets 3.6.0
+- Tokenizers 0.21.1

best/config.json

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+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "fully human-written",
+    "1": "human-written, then machine-polished",
+    "2": "machine-written, then machine-humanized",
+    "3": "human-initiated, then machine-continued",
+    "4": "deeply-mixed text; where some parts are written by a human and some are generated by a machine",
+    "5": "machine-written, then human-edited"
+  },
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+  "intermediate_size": 3072,
+  "label2id": {
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+    "fully human-written": 0,
+    "human-initiated, then machine-continued": 3,
+    "human-written, then machine-polished": 1,
+    "machine-written, then human-edited": 5,
+    "machine-written, then machine-humanized": 2
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.51.3",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 50265
+}

best/model.safetensors

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best/special_tokens_map.json

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best/tokenizer_config.json

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config.json

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+  "hidden_act": "gelu",
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+    "2": "machine-written, then machine-humanized",
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+    "4": "deeply-mixed text; where some parts are written by a human and some are generated by a machine",
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+    "machine-written, then human-edited": 5,
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+  "problem_type": "single_label_classification",
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special_tokens_map.json

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tokenizer_config.json

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