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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: albert/albert-base-v2 |
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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: Albert-Base |
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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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# Albert-Base |
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This model is a fine-tuned version of [albert/albert-base-v2](https://huggingface.co/albert/albert-base-v2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2950 |
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- Accuracy: 0.9234 |
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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: 5e-05 |
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- train_batch_size: 128 |
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- eval_batch_size: 512 |
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- seed: 42 |
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- optimizer: Use adamw_torch 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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- num_epochs: 40 |
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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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| 0.4359 | 1.0 | 158 | 0.3263 | 0.9016 | |
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| 0.2711 | 2.0 | 316 | 0.3180 | 0.9063 | |
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| 0.1583 | 3.0 | 474 | 0.3126 | 0.9117 | |
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| 0.1463 | 4.0 | 632 | 0.3113 | 0.9132 | |
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| 0.0722 | 5.0 | 790 | 0.2950 | 0.9234 | |
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| 0.0627 | 6.0 | 948 | 0.3461 | 0.9178 | |
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| 0.0528 | 7.0 | 1106 | 0.3541 | 0.9177 | |
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| 0.0336 | 8.0 | 1264 | 0.3469 | 0.9251 | |
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| 0.0416 | 9.0 | 1422 | 0.4367 | 0.9130 | |
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| 0.0356 | 10.0 | 1580 | 0.3814 | 0.9226 | |
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| 0.0092 | 11.0 | 1738 | 0.4591 | 0.9206 | |
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| 0.0127 | 12.0 | 1896 | 0.4355 | 0.9277 | |
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| 0.0055 | 13.0 | 2054 | 0.4419 | 0.9264 | |
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| 0.0019 | 14.0 | 2212 | 0.4578 | 0.9297 | |
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| 0.0009 | 15.0 | 2370 | 0.4947 | 0.9284 | |
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| 0.0017 | 16.0 | 2528 | 0.4893 | 0.9318 | |
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| 0.0003 | 17.0 | 2686 | 0.5132 | 0.9278 | |
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| 0.0013 | 18.0 | 2844 | 0.4901 | 0.9307 | |
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| 0.0029 | 19.0 | 3002 | 0.5176 | 0.9301 | |
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| 0.0064 | 20.0 | 3160 | 0.5325 | 0.9321 | |
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| 0.0001 | 21.0 | 3318 | 0.5367 | 0.9294 | |
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| 0.0001 | 22.0 | 3476 | 0.5389 | 0.9309 | |
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| 0.008 | 23.0 | 3634 | 0.5888 | 0.9274 | |
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| 0.0001 | 24.0 | 3792 | 0.5542 | 0.9315 | |
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| 0.0003 | 25.0 | 3950 | 0.5350 | 0.9323 | |
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| 0.0 | 26.0 | 4108 | 0.5480 | 0.9312 | |
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| 0.0 | 27.0 | 4266 | 0.5337 | 0.9343 | |
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| 0.0 | 28.0 | 4424 | 0.5453 | 0.9331 | |
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| 0.0 | 29.0 | 4582 | 0.5434 | 0.9333 | |
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| 0.0 | 30.0 | 4740 | 0.5443 | 0.9335 | |
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| 0.0 | 31.0 | 4898 | 0.5457 | 0.9338 | |
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| 0.0 | 32.0 | 5056 | 0.5468 | 0.9339 | |
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| 0.0 | 33.0 | 5214 | 0.5481 | 0.9339 | |
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| 0.0 | 34.0 | 5372 | 0.5492 | 0.9339 | |
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| 0.0 | 35.0 | 5530 | 0.5503 | 0.9343 | |
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| 0.0 | 36.0 | 5688 | 0.5511 | 0.9345 | |
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| 0.0 | 37.0 | 5846 | 0.5519 | 0.9343 | |
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| 0.0 | 38.0 | 6004 | 0.5525 | 0.9343 | |
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| 0.0 | 39.0 | 6162 | 0.5529 | 0.9343 | |
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| 0.0 | 40.0 | 6320 | 0.5530 | 0.9343 | |
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### Framework versions |
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- Transformers 4.49.0 |
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- Pytorch 2.6.0+cu124 |
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- Tokenizers 0.21.0 |
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