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--- |
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license: apache-2.0 |
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base_model: alex-miller/ODABert |
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tags: |
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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: iati-gender-multi-classifier-weighted-minitest |
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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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# iati-gender-multi-classifier-weighted-minitest |
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This model is a fine-tuned version of [alex-miller/ODABert](https://huggingface.co/alex-miller/ODABert) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6625 |
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- Accuracy: 0.8256 |
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- F1: 0.6997 |
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- Precision: 0.6138 |
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- Recall: 0.8135 |
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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-06 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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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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| 0.9142 | 1.0 | 616 | 0.7573 | 0.7352 | 0.5803 | 0.4802 | 0.7331 | |
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| 0.7431 | 2.0 | 1232 | 0.6871 | 0.7973 | 0.6652 | 0.5661 | 0.8062 | |
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| 0.6934 | 3.0 | 1848 | 0.6713 | 0.8160 | 0.6902 | 0.5955 | 0.8208 | |
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| 0.6631 | 4.0 | 2464 | 0.6609 | 0.8187 | 0.6944 | 0.5997 | 0.8245 | |
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| 0.6341 | 5.0 | 3080 | 0.6589 | 0.8237 | 0.6956 | 0.6117 | 0.8062 | |
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| 0.6143 | 6.0 | 3696 | 0.6551 | 0.8205 | 0.6970 | 0.6027 | 0.8263 | |
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| 0.5931 | 7.0 | 4312 | 0.6597 | 0.8201 | 0.6893 | 0.6061 | 0.7989 | |
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| 0.5773 | 8.0 | 4928 | 0.6579 | 0.8224 | 0.6963 | 0.6076 | 0.8154 | |
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| 0.5652 | 9.0 | 5544 | 0.6613 | 0.8233 | 0.6984 | 0.6087 | 0.8190 | |
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| 0.5597 | 10.0 | 6160 | 0.6625 | 0.8256 | 0.6997 | 0.6138 | 0.8135 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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