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--- |
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library_name: transformers |
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license: mit |
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base_model: facebook/w2v-bert-2.0 |
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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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model-index: |
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- name: muk-english-digits-classification |
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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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# muk-english-digits-classification |
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This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8012 |
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- Accuracy: 1.0 |
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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: 8 |
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- eval_batch_size: 1 |
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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_ratio: 0.1 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 2.3974 | 1.0 | 32 | 2.3805 | 0.1875 | |
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| 2.3542 | 2.0 | 64 | 2.3080 | 0.1875 | |
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| 2.2986 | 3.0 | 96 | 2.1997 | 0.3438 | |
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| 2.1947 | 4.0 | 128 | 2.0517 | 0.4062 | |
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| 2.0741 | 5.0 | 160 | 1.9182 | 0.4062 | |
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| 1.9479 | 6.0 | 192 | 1.8475 | 0.4688 | |
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| 1.8934 | 7.0 | 224 | 1.6724 | 0.5938 | |
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| 1.687 | 8.0 | 256 | 1.5422 | 0.6875 | |
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| 1.5745 | 9.0 | 288 | 1.3878 | 0.875 | |
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| 1.5288 | 10.0 | 320 | 1.2905 | 0.875 | |
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| 1.3518 | 11.0 | 352 | 1.1875 | 0.9375 | |
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| 1.2558 | 12.0 | 384 | 1.0936 | 0.9375 | |
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| 1.1538 | 13.0 | 416 | 1.0296 | 0.9688 | |
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| 1.186 | 14.0 | 448 | 0.9815 | 0.9688 | |
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| 1.033 | 15.0 | 480 | 0.9271 | 1.0 | |
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| 0.9828 | 16.0 | 512 | 0.8811 | 1.0 | |
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| 0.995 | 17.0 | 544 | 0.8454 | 0.9688 | |
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| 0.9213 | 18.0 | 576 | 0.8176 | 1.0 | |
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| 0.9313 | 19.0 | 608 | 0.8048 | 1.0 | |
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| 0.9029 | 20.0 | 640 | 0.8012 | 1.0 | |
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### Framework versions |
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- Transformers 4.57.2 |
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- Pytorch 2.9.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.22.1 |
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