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--- |
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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: bert_12_layer_model_v1_complete_training |
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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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# bert_12_layer_model_v1_complete_training |
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This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7148 |
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- Accuracy: 0.6576 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 10 |
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- distributed_type: multi-GPU |
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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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- lr_scheduler_warmup_steps: 10000 |
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- num_epochs: 5 |
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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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| 6.1779 | 0.11 | 10000 | 6.1719 | 0.1487 | |
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| 4.6914 | 0.22 | 20000 | 4.5039 | 0.3178 | |
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| 3.2325 | 0.33 | 30000 | 3.0977 | 0.4772 | |
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| 2.831 | 0.44 | 40000 | 2.7266 | 0.5224 | |
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| 2.6262 | 0.55 | 50000 | 2.5371 | 0.5455 | |
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| 2.5006 | 0.66 | 60000 | 2.4141 | 0.5614 | |
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| 2.4062 | 0.76 | 70000 | 2.3242 | 0.5734 | |
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| 2.3338 | 0.87 | 80000 | 2.2539 | 0.5823 | |
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| 2.2838 | 0.98 | 90000 | 2.2012 | 0.5894 | |
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| 2.231 | 1.09 | 100000 | 2.1504 | 0.5959 | |
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| 2.1903 | 1.2 | 110000 | 2.1133 | 0.6009 | |
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| 2.1594 | 1.31 | 120000 | 2.0801 | 0.6054 | |
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| 2.1307 | 1.42 | 130000 | 2.0488 | 0.6095 | |
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| 2.0948 | 1.53 | 140000 | 2.0234 | 0.6133 | |
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| 2.0748 | 1.64 | 150000 | 1.9980 | 0.6169 | |
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| 2.0572 | 1.75 | 160000 | 1.9756 | 0.6195 | |
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| 2.0359 | 1.86 | 170000 | 1.9551 | 0.6225 | |
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| 2.0148 | 1.97 | 180000 | 1.9385 | 0.6251 | |
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| 1.9994 | 2.08 | 190000 | 1.9219 | 0.6274 | |
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| 1.9769 | 2.18 | 200000 | 1.9043 | 0.6297 | |
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| 1.9705 | 2.29 | 210000 | 1.8916 | 0.6317 | |
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| 1.9557 | 2.4 | 220000 | 1.8779 | 0.6338 | |
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| 1.9407 | 2.51 | 230000 | 1.8643 | 0.6354 | |
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| 1.9307 | 2.62 | 240000 | 1.8525 | 0.6372 | |
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| 1.9186 | 2.73 | 250000 | 1.8408 | 0.6388 | |
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| 1.9114 | 2.84 | 260000 | 1.8320 | 0.6401 | |
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| 1.896 | 2.95 | 270000 | 1.8213 | 0.6419 | |
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| 1.8857 | 3.06 | 280000 | 1.8115 | 0.6433 | |
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| 1.8752 | 3.17 | 290000 | 1.8037 | 0.6443 | |
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| 1.8662 | 3.28 | 300000 | 1.7949 | 0.6457 | |
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| 1.8575 | 3.39 | 310000 | 1.7871 | 0.6470 | |
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| 1.8538 | 3.5 | 320000 | 1.7793 | 0.6478 | |
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| 1.8426 | 3.6 | 330000 | 1.7734 | 0.6489 | |
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| 1.8389 | 3.71 | 340000 | 1.7646 | 0.6501 | |
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| 1.8278 | 3.82 | 350000 | 1.7598 | 0.6511 | |
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| 1.8319 | 3.93 | 360000 | 1.7529 | 0.6520 | |
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| 1.8203 | 4.04 | 370000 | 1.7471 | 0.6527 | |
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| 1.8162 | 4.15 | 380000 | 1.7412 | 0.6536 | |
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| 1.8113 | 4.26 | 390000 | 1.7373 | 0.6543 | |
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| 1.8055 | 4.37 | 400000 | 1.7324 | 0.6551 | |
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| 1.7991 | 4.48 | 410000 | 1.7285 | 0.6556 | |
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| 1.7965 | 4.59 | 420000 | 1.7246 | 0.6562 | |
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| 1.7938 | 4.7 | 430000 | 1.7207 | 0.6567 | |
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| 1.793 | 4.81 | 440000 | 1.7178 | 0.6571 | |
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| 1.7848 | 4.92 | 450000 | 1.7148 | 0.6576 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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