v3: multi-task with hard example mining
Browse files- README.md +85 -0
- model.safetensors +1 -1
README.md
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---
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library_name: transformers
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tags:
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- trackio
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- trackio:https://huggingface.co/spaces/ciphertext/trackio
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- generated_from_trainer
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metrics:
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- accuracy
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- f1
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- precision
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- recall
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model-index:
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- name: vijil-bias-detector-v4
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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<a href="https://huggingface.co/spaces/ciphertext/trackio" target="_blank"><img src="https://raw.githubusercontent.com/gradio-app/trackio/refs/heads/main/trackio/assets/badge.png" alt="Visualize in Trackio" title="Visualize in Trackio" style="height: 40px;"/></a>
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# vijil-bias-detector-v4
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This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1877
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- Accuracy: 0.9050
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- F1: 0.9094
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- Precision: 0.8983
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- Recall: 0.9207
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 32
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- eval_batch_size: 64
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 0.1
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- num_epochs: 5
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| 0.5963 | 0.3221 | 200 | 0.4896 | 0.7339 | 0.7245 | 0.7808 | 0.6757 |
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| 0.3916 | 0.6441 | 400 | 0.3866 | 0.7681 | 0.7700 | 0.7915 | 0.7496 |
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| 0.3415 | 0.9662 | 600 | 0.3335 | 0.7959 | 0.8076 | 0.7887 | 0.8274 |
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| 0.3058 | 1.2882 | 800 | 0.3029 | 0.8172 | 0.8225 | 0.8270 | 0.8180 |
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| 0.2417 | 1.6103 | 1000 | 0.2334 | 0.8720 | 0.8797 | 0.8564 | 0.9044 |
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| 0.2137 | 1.9324 | 1200 | 0.2192 | 0.8853 | 0.8891 | 0.8901 | 0.8880 |
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| 0.1833 | 2.2544 | 1400 | 0.2099 | 0.8921 | 0.9011 | 0.8574 | 0.9495 |
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| 0.1805 | 2.5765 | 1600 | 0.2022 | 0.8937 | 0.8992 | 0.8831 | 0.9160 |
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| 0.1733 | 2.8986 | 1800 | 0.2048 | 0.8869 | 0.8861 | 0.9255 | 0.8499 |
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| 0.1473 | 3.2206 | 2000 | 0.1850 | 0.9058 | 0.9116 | 0.8868 | 0.9378 |
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| 0.1271 | 3.5427 | 2200 | 0.1941 | 0.9066 | 0.9121 | 0.8892 | 0.9362 |
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| 0.1159 | 3.8647 | 2400 | 0.1865 | 0.9070 | 0.9108 | 0.9042 | 0.9176 |
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| 0.0996 | 4.1868 | 2600 | 0.1906 | 0.9034 | 0.9076 | 0.8986 | 0.9168 |
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| 0.1017 | 4.5089 | 2800 | 0.1923 | 0.9022 | 0.9078 | 0.8866 | 0.9300 |
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| 0.0952 | 4.8309 | 3000 | 0.1902 | 0.9046 | 0.9099 | 0.8905 | 0.9300 |
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| 0.0945 | 5.0 | 3105 | 0.1877 | 0.9050 | 0.9094 | 0.8983 | 0.9207 |
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### Framework versions
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- Transformers 5.5.0
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- Pytorch 2.11.0+cu130
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- Datasets 4.8.4
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- Tokenizers 0.22.2
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model.safetensors
CHANGED
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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size 596095760
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version https://git-lfs.github.com/spec/v1
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oid sha256:6557cb8f84a70cfe2485d31985aad00e0ded272dab253d5bb5583ad296cd4b31
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size 596095760
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