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--- |
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license: apache-2.0 |
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base_model: google-bert/bert-base-uncased |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: Google_bert-base-uncased |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/dhanishetty-personaluse/huggingface/runs/5uvs4op2) |
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# Google_bert-base-uncased |
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This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/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: 0.0596 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: inverse_sqrt |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 2.2234 | 0.024 | 30 | 0.9557 | |
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| 0.4601 | 0.048 | 60 | 0.4359 | |
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| 0.3149 | 0.072 | 90 | 0.2795 | |
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| 0.2403 | 0.096 | 120 | 0.2142 | |
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| 0.1876 | 0.12 | 150 | 0.1714 | |
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| 0.1691 | 0.144 | 180 | 0.1488 | |
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| 0.1394 | 0.168 | 210 | 0.1273 | |
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| 0.1264 | 0.192 | 240 | 0.1160 | |
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| 0.1113 | 0.216 | 270 | 0.1079 | |
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| 0.1148 | 0.24 | 300 | 0.0992 | |
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| 0.0995 | 0.264 | 330 | 0.0940 | |
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| 0.096 | 0.288 | 360 | 0.0941 | |
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| 0.0954 | 0.312 | 390 | 0.0854 | |
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| 0.089 | 0.336 | 420 | 0.0899 | |
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| 0.0826 | 0.36 | 450 | 0.0841 | |
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| 0.0872 | 0.384 | 480 | 0.0811 | |
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| 0.0794 | 0.408 | 510 | 0.0759 | |
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| 0.0756 | 0.432 | 540 | 0.0766 | |
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| 0.0826 | 0.456 | 570 | 0.0729 | |
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| 0.0841 | 0.48 | 600 | 0.0715 | |
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| 0.076 | 0.504 | 630 | 0.0737 | |
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| 0.0746 | 0.528 | 660 | 0.0691 | |
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| 0.0719 | 0.552 | 690 | 0.0697 | |
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| 0.0722 | 0.576 | 720 | 0.0673 | |
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| 0.0713 | 0.6 | 750 | 0.0656 | |
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| 0.0671 | 0.624 | 780 | 0.0652 | |
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| 0.0741 | 0.648 | 810 | 0.0675 | |
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| 0.0723 | 0.672 | 840 | 0.0663 | |
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| 0.0687 | 0.696 | 870 | 0.0649 | |
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| 0.067 | 0.72 | 900 | 0.0637 | |
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| 0.0623 | 0.744 | 930 | 0.0643 | |
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| 0.0599 | 0.768 | 960 | 0.0643 | |
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| 0.0686 | 0.792 | 990 | 0.0624 | |
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| 0.0638 | 0.816 | 1020 | 0.0623 | |
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| 0.0565 | 0.84 | 1050 | 0.0626 | |
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| 0.0614 | 0.864 | 1080 | 0.0615 | |
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| 0.063 | 0.888 | 1110 | 0.0592 | |
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| 0.0592 | 0.912 | 1140 | 0.0618 | |
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| 0.0687 | 0.936 | 1170 | 0.0618 | |
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| 0.0577 | 0.96 | 1200 | 0.0600 | |
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| 0.0629 | 0.984 | 1230 | 0.0596 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.3.1+cu118 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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