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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-large-uncased-finetuned-vi-infovqa |
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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-large-uncased-finetuned-vi-infovqa |
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This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 7.4878 |
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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: 2 |
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- eval_batch_size: 2 |
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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: 6 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| No log | 0.11 | 100 | 4.6256 | |
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| No log | 0.21 | 200 | 4.4042 | |
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| No log | 0.32 | 300 | 5.0021 | |
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| No log | 0.43 | 400 | 4.2825 | |
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| 4.6758 | 0.53 | 500 | 4.3886 | |
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| 4.6758 | 0.64 | 600 | 4.2519 | |
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| 4.6758 | 0.75 | 700 | 4.2977 | |
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| 4.6758 | 0.85 | 800 | 3.9916 | |
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| 4.6758 | 0.96 | 900 | 4.1650 | |
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| 4.1715 | 1.07 | 1000 | 4.5001 | |
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| 4.1715 | 1.17 | 1100 | 4.0898 | |
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| 4.1715 | 1.28 | 1200 | 4.1623 | |
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| 4.1715 | 1.39 | 1300 | 4.3271 | |
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| 4.1715 | 1.49 | 1400 | 3.9661 | |
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| 3.7926 | 1.6 | 1500 | 3.8727 | |
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| 3.7926 | 1.71 | 1600 | 3.8934 | |
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| 3.7926 | 1.81 | 1700 | 3.7262 | |
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| 3.7926 | 1.92 | 1800 | 3.7701 | |
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| 3.7926 | 2.03 | 1900 | 3.7653 | |
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| 3.5041 | 2.13 | 2000 | 3.9261 | |
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| 3.5041 | 2.24 | 2100 | 4.0915 | |
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| 3.5041 | 2.35 | 2200 | 4.0348 | |
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| 3.5041 | 2.45 | 2300 | 4.0212 | |
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| 3.5041 | 2.56 | 2400 | 4.4653 | |
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| 2.8475 | 2.67 | 2500 | 4.2959 | |
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| 2.8475 | 2.77 | 2600 | 4.1039 | |
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| 2.8475 | 2.88 | 2700 | 3.8037 | |
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| 2.8475 | 2.99 | 2800 | 3.7552 | |
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| 2.8475 | 3.09 | 2900 | 4.2476 | |
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| 2.5488 | 3.2 | 3000 | 4.6716 | |
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| 2.5488 | 3.3 | 3100 | 4.7058 | |
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| 2.5488 | 3.41 | 3200 | 4.6266 | |
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| 2.5488 | 3.52 | 3300 | 4.5697 | |
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| 2.5488 | 3.62 | 3400 | 5.1017 | |
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| 2.0347 | 3.73 | 3500 | 4.6254 | |
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| 2.0347 | 3.84 | 3600 | 4.4822 | |
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| 2.0347 | 3.94 | 3700 | 4.9413 | |
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| 2.0347 | 4.05 | 3800 | 5.3600 | |
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| 2.0347 | 4.16 | 3900 | 5.7323 | |
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| 1.6566 | 4.26 | 4000 | 5.8822 | |
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| 1.6566 | 4.37 | 4100 | 6.0173 | |
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| 1.6566 | 4.48 | 4200 | 5.6688 | |
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| 1.6566 | 4.58 | 4300 | 6.0617 | |
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| 1.6566 | 4.69 | 4400 | 6.6631 | |
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| 1.3348 | 4.8 | 4500 | 6.0290 | |
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| 1.3348 | 4.9 | 4600 | 6.2455 | |
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| 1.3348 | 5.01 | 4700 | 6.0963 | |
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| 1.3348 | 5.12 | 4800 | 7.0983 | |
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| 1.3348 | 5.22 | 4900 | 7.5483 | |
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| 1.0701 | 5.33 | 5000 | 7.7187 | |
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| 1.0701 | 5.44 | 5100 | 7.4630 | |
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| 1.0701 | 5.54 | 5200 | 7.1394 | |
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| 1.0701 | 5.65 | 5300 | 7.0703 | |
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| 1.0701 | 5.76 | 5400 | 7.5611 | |
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| 0.9414 | 5.86 | 5500 | 7.6038 | |
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| 0.9414 | 5.97 | 5600 | 7.4878 | |
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### Framework versions |
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- Transformers 4.15.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.17.0 |
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- Tokenizers 0.10.3 |
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