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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_1000exs_20timesteps_run |
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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_1000exs_20timesteps_run |
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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: 0.8330 |
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- Accuracy: 0.51 |
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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: 64 |
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- eval_batch_size: 64 |
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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 | 16 | 3052559.25 | 0.51 | |
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| No log | 2.0 | 32 | 2330149.0 | 0.51 | |
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| No log | 3.0 | 48 | 1716418.75 | 0.51 | |
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| No log | 4.0 | 64 | 1113477.0 | 0.51 | |
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| No log | 5.0 | 80 | 524712.25 | 0.51 | |
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| No log | 6.0 | 96 | 36429.3633 | 0.51 | |
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| No log | 7.0 | 112 | 5025.1558 | 0.51 | |
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| No log | 8.0 | 128 | 2793.7087 | 0.51 | |
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| No log | 9.0 | 144 | 173.9886 | 0.51 | |
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| No log | 10.0 | 160 | 1.6353 | 0.49 | |
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| No log | 11.0 | 176 | 1.2341 | 0.49 | |
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| No log | 12.0 | 192 | 0.9290 | 0.49 | |
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| No log | 13.0 | 208 | 0.7376 | 0.49 | |
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| No log | 14.0 | 224 | 0.7311 | 0.51 | |
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| No log | 15.0 | 240 | 0.8214 | 0.51 | |
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| No log | 16.0 | 256 | 0.8330 | 0.51 | |
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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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