| --- |
| library_name: transformers |
| license: mit |
| base_model: jhu-clsp/mmBERT-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: translation-source-classifier |
| 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. --> |
|
|
| # translation-source-classifier |
|
|
| This model is a fine-tuned version of [jhu-clsp/mmBERT-base](https://huggingface.co/jhu-clsp/mmBERT-base) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.5460 |
| - Accuracy: 0.6111 |
|
|
| ## Model description |
|
|
| More information needed |
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|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
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|
| The following hyperparameters were used during training: |
| - learning_rate: 0.001 |
| - train_batch_size: 128 |
| - eval_batch_size: 128 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 10 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:------:|:---------------:|:--------:| |
| | 2.1867 | 1.0 | 14063 | 2.2778 | 0.4457 | |
| | 2.0165 | 2.0 | 28126 | 2.0671 | 0.4984 | |
| | 1.935 | 3.0 | 42189 | 1.9881 | 0.5151 | |
| | 1.8636 | 4.0 | 56252 | 1.8941 | 0.5351 | |
| | 1.7705 | 5.0 | 70315 | 1.8231 | 0.5460 | |
| | 1.7174 | 6.0 | 84378 | 1.7304 | 0.5691 | |
| | 1.6526 | 7.0 | 98441 | 1.6755 | 0.5788 | |
| | 1.6009 | 8.0 | 112504 | 1.6174 | 0.5922 | |
| | 1.4959 | 9.0 | 126567 | 1.5779 | 0.6025 | |
| | 1.4539 | 10.0 | 140630 | 1.5460 | 0.6111 | |
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| ### Framework versions |
|
|
| - Transformers 4.57.6 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.8.4 |
| - Tokenizers 0.22.2 |
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|
