arincon/ia-detection-tiny-random-gptj

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- autextification2023
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: ia-detection-tiny-random-gptj
+  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: 0.633198973983144
+    - name: F1
+      type: f1
+      value: 0.7005683517798384
+    - name: Precision
+      type: precision
+      value: 0.6022888003086023
+    - name: Recall
+      type: recall
+      value: 0.8371760500446828
+---
+
+<!-- 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-tiny-random-gptj
+
+This model is a fine-tuned version of [ydshieh/tiny-random-gptj-for-sequence-classification](https://huggingface.co/ydshieh/tiny-random-gptj-for-sequence-classification) on the autextification2023 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7313
+- Accuracy: 0.6332
+- F1: 0.7006
+- Precision: 0.6023
+- Recall: 0.8372
+
+## 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.6038        | 1.0   | 3808  | 0.5362          | 0.7309   | 0.7270 | 0.7294    | 0.7246 |
+| 0.5303        | 2.0   | 7616  | 0.5109          | 0.7465   | 0.7358 | 0.7592    | 0.7139 |
+| 0.4588        | 3.0   | 11424 | 0.5258          | 0.7424   | 0.7568 | 0.7097    | 0.8106 |
+| 0.4459        | 4.0   | 15232 | 0.5137          | 0.7477   | 0.7428 | 0.7491    | 0.7366 |
+| 0.3586        | 5.0   | 19040 | 0.5062          | 0.7572   | 0.7452 | 0.7745    | 0.7180 |
+| 0.4072        | 6.0   | 22848 | 0.5264          | 0.7539   | 0.7565 | 0.7407    | 0.7730 |
+
+
+### Framework versions
+
+- Transformers 4.26.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.13.3

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