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bert-base-uncased-finetuned-vi-infovqa

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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: bert-base-uncased-finetuned-vi-infovqa
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+ results: []
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+ ---
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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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+
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+ # bert-base-uncased-finetuned-vi-infovqa
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+
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+ This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 13.9895
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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+ - seed: 250500
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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: 50
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:-----:|:---------------:|
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+ | 4.3635 | 1.07 | 500 | 4.5286 |
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+ | 3.8961 | 2.13 | 1000 | 4.4055 |
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+ | 3.3012 | 3.2 | 1500 | 5.0429 |
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+ | 2.5998 | 4.26 | 2000 | 5.4774 |
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+ | 1.8851 | 5.33 | 2500 | 6.4376 |
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+ | 1.3968 | 6.4 | 3000 | 6.8778 |
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+ | 1.1244 | 7.46 | 3500 | 7.1008 |
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+ | 0.8851 | 8.53 | 4000 | 6.8303 |
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+ | 0.7654 | 9.59 | 4500 | 8.6628 |
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+ | 0.6895 | 10.66 | 5000 | 6.0228 |
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+ | 0.5989 | 11.73 | 5500 | 8.8191 |
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+ | 0.6033 | 12.79 | 6000 | 9.7359 |
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+ | 0.6005 | 13.86 | 6500 | 7.6668 |
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+ | 0.522 | 14.93 | 7000 | 8.7185 |
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+ | 0.464 | 15.99 | 7500 | 10.1035 |
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+ | 0.4112 | 17.06 | 8000 | 8.7928 |
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+ | 0.3501 | 18.12 | 8500 | 9.9157 |
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+ | 0.3401 | 19.19 | 9000 | 12.1013 |
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+ | 0.3233 | 20.26 | 9500 | 10.2730 |
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+ | 0.2513 | 21.32 | 10000 | 8.4839 |
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+ | 0.2319 | 22.39 | 10500 | 10.9367 |
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+ | 0.2269 | 23.45 | 11000 | 9.6821 |
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+ | 0.237 | 24.52 | 11500 | 10.2357 |
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+ | 0.1868 | 25.59 | 12000 | 9.8762 |
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+ | 0.1655 | 26.65 | 12500 | 10.7398 |
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+ | 0.1561 | 27.72 | 13000 | 11.8157 |
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+ | 0.1714 | 28.78 | 13500 | 10.8686 |
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+ | 0.1098 | 29.85 | 14000 | 13.1537 |
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+ | 0.1222 | 30.92 | 14500 | 14.5398 |
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+ | 0.1325 | 31.98 | 15000 | 12.6095 |
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+ | 0.1088 | 33.05 | 15500 | 12.0747 |
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+ | 0.0855 | 34.12 | 16000 | 12.4450 |
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+ | 0.0832 | 35.18 | 16500 | 12.9436 |
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+ | 0.0687 | 36.25 | 17000 | 12.5902 |
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+ | 0.0804 | 37.31 | 17500 | 11.9873 |
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+ | 0.0427 | 38.38 | 18000 | 12.6357 |
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+ | 0.0529 | 39.45 | 18500 | 11.5851 |
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+ | 0.0478 | 40.51 | 19000 | 13.1796 |
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+ | 0.0513 | 41.58 | 19500 | 13.8597 |
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+ | 0.0449 | 42.64 | 20000 | 13.6467 |
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+ | 0.0327 | 43.71 | 20500 | 13.0391 |
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+ | 0.0329 | 44.78 | 21000 | 13.1984 |
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+ | 0.0266 | 45.84 | 21500 | 13.9690 |
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+ | 0.0301 | 46.91 | 22000 | 13.9516 |
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+ | 0.0193 | 47.97 | 22500 | 13.9104 |
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+ | 0.0273 | 49.04 | 23000 | 13.9895 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.14.1
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+ - Pytorch 1.10.0+cu111
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+ - Datasets 1.16.1
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+ - Tokenizers 0.10.3