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--- |
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license: apache-2.0 |
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base_model: google/mobilebert-uncased |
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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: mobilebert_500exs_10timesteps_run0 |
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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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# mobilebert_500exs_10timesteps_run0 |
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This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7313 |
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- Accuracy: 0.48 |
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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: 8 |
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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: 16 |
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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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| No log | 1.0 | 63 | 0.7190 | 0.53 | |
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| No log | 2.0 | 126 | 0.7219 | 0.47 | |
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| No log | 3.0 | 189 | 0.6946 | 0.53 | |
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| No log | 4.0 | 252 | 0.7081 | 0.46 | |
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| No log | 5.0 | 315 | 0.7062 | 0.47 | |
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| No log | 6.0 | 378 | 0.7014 | 0.47 | |
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| No log | 7.0 | 441 | 0.7058 | 0.46 | |
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| 70646.992 | 8.0 | 504 | 0.6969 | 0.54 | |
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| 70646.992 | 9.0 | 567 | 0.7082 | 0.44 | |
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| 70646.992 | 10.0 | 630 | 0.8435 | 0.47 | |
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| 70646.992 | 11.0 | 693 | 0.7574 | 0.47 | |
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| 70646.992 | 12.0 | 756 | 0.6926 | 0.55 | |
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| 70646.992 | 13.0 | 819 | 0.7150 | 0.47 | |
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| 70646.992 | 14.0 | 882 | 0.7133 | 0.51 | |
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| 70646.992 | 15.0 | 945 | 0.7492 | 0.47 | |
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| 0.6741 | 16.0 | 1008 | 0.7313 | 0.48 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.0+cu118 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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