arincon/ia-detection-roberta-base

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+datasets:
+- autextification2023
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: ia-detection-roberta-base
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: autextification2023
+      type: autextification2023
+      config: detection_en
+      split: train
+      args: detection_en
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.512550384756321
+    - name: F1
+      type: f1
+      value: 0.6777299981830295
+    - name: Precision
+      type: precision
+      value: 0.512550384756321
+    - name: Recall
+      type: recall
+      value: 1.0
+---
+
+<!-- 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. -->
+
+# ia-detection-roberta-base
+
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the autextification2023 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6928
+- Accuracy: 0.5126
+- F1: 0.6777
+- Precision: 0.5126
+- Recall: 1.0
+
+## 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: 0.0001
+- 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.7021        | 1.0   | 3808  | 0.6950          | 0.5052   | 0.0    | 0.0       | 0.0    |
+| 0.6936        | 2.0   | 7616  | 0.6937          | 0.4948   | 0.6621 | 0.4948    | 1.0    |
+| 0.692         | 3.0   | 11424 | 0.6936          | 0.5052   | 0.0    | 0.0       | 0.0    |
+| 0.6988        | 4.0   | 15232 | 0.6952          | 0.4948   | 0.6621 | 0.4948    | 1.0    |
+| 0.6951        | 5.0   | 19040 | 0.6931          | 0.5052   | 0.0    | 0.0       | 0.0    |
+
+
+### Framework versions
+
+- Transformers 4.26.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.13.3

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special_tokens_map.json

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+{
+  "bos_token": "<s>",
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "mask_token": {
+    "content": "<mask>",
+    "lstrip": true,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
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+  "unk_token": "<unk>"
+}

tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "bos_token": "<s>",
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "errors": "replace",
+  "mask_token": "<mask>",
+  "model_max_length": 512,
+  "name_or_path": "roberta-base",
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "special_tokens_map_file": null,
+  "tokenizer_class": "RobertaTokenizer",
+  "trim_offsets": true,
+  "unk_token": "<unk>"
+}