Model card error
There’s an error in the yaml metadata in this model card. If you’re the model author, please log in to check the list of errors and warnings.
bert-large-uncased-finetuned-docvqa
This model is a fine-tuned version of bert-large-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.6367
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 250500
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.5228 | 0.05 | 1000 | 2.6645 |
2.4909 | 0.1 | 2000 | 2.8985 |
2.1679 | 0.16 | 3000 | 2.3551 |
1.9451 | 0.21 | 4000 | 2.2226 |
1.6814 | 0.26 | 5000 | 2.1590 |
1.8868 | 0.31 | 6000 | 2.6197 |
1.6618 | 0.36 | 7000 | 2.3632 |
1.8313 | 0.41 | 8000 | 2.4519 |
1.7017 | 0.47 | 9000 | 2.2682 |
1.8169 | 0.52 | 10000 | 2.4486 |
1.7074 | 0.57 | 11000 | 2.3862 |
1.7674 | 0.62 | 12000 | 2.1801 |
1.8134 | 0.67 | 13000 | 2.3032 |
1.8334 | 0.73 | 14000 | 2.4205 |
1.6819 | 0.78 | 15000 | 2.2398 |
1.5846 | 0.83 | 16000 | 2.3834 |
1.6758 | 0.88 | 17000 | 1.9683 |
1.6303 | 0.93 | 18000 | 2.3297 |
1.5652 | 0.98 | 19000 | 2.0581 |
1.3045 | 1.04 | 20000 | 2.4950 |
1.2393 | 1.09 | 21000 | 2.6622 |
1.1526 | 1.14 | 22000 | 2.3749 |
1.2631 | 1.19 | 23000 | 2.3915 |
1.1846 | 1.24 | 24000 | 2.2592 |
1.2731 | 1.3 | 25000 | 2.4239 |
1.3057 | 1.35 | 26000 | 2.2920 |
1.134 | 1.4 | 27000 | 2.3107 |
1.2017 | 1.45 | 28000 | 2.4271 |
1.2202 | 1.5 | 29000 | 2.1814 |
1.2179 | 1.56 | 30000 | 2.3365 |
1.2359 | 1.61 | 31000 | 2.1256 |
1.1964 | 1.66 | 32000 | 2.1720 |
1.269 | 1.71 | 33000 | 2.4363 |
1.1812 | 1.76 | 34000 | 2.2372 |
1.2187 | 1.81 | 35000 | 2.2318 |
1.1805 | 1.87 | 36000 | 2.3693 |
1.1458 | 1.92 | 37000 | 2.5128 |
1.1958 | 1.97 | 38000 | 2.1311 |
0.8924 | 2.02 | 39000 | 2.4635 |
0.869 | 2.07 | 40000 | 2.8231 |
0.8333 | 2.13 | 41000 | 2.6762 |
0.9194 | 2.18 | 42000 | 2.4588 |
0.8089 | 2.23 | 43000 | 2.6443 |
0.8612 | 2.28 | 44000 | 2.4300 |
0.7981 | 2.33 | 45000 | 2.7418 |
0.9765 | 2.38 | 46000 | 2.6543 |
0.8646 | 2.44 | 47000 | 2.5990 |
1.0316 | 2.49 | 48000 | 2.4625 |
0.9862 | 2.54 | 49000 | 2.4691 |
1.027 | 2.59 | 50000 | 2.4156 |
0.9412 | 2.64 | 51000 | 2.4204 |
0.9353 | 2.7 | 52000 | 2.4933 |
0.9509 | 2.75 | 53000 | 2.4708 |
0.9351 | 2.8 | 54000 | 2.5351 |
0.9968 | 2.85 | 55000 | 2.2506 |
1.025 | 2.9 | 56000 | 2.6317 |
1.627 | 2.95 | 57000 | 2.7843 |
0.9294 | 3.01 | 58000 | 2.9396 |
0.6043 | 3.06 | 59000 | 3.1560 |
0.7903 | 3.11 | 60000 | 2.8330 |
0.7373 | 3.16 | 61000 | 2.9422 |
0.6499 | 3.21 | 62000 | 3.0948 |
0.6411 | 3.27 | 63000 | 2.7900 |
0.625 | 3.32 | 64000 | 2.5268 |
0.6264 | 3.37 | 65000 | 2.8701 |
0.6143 | 3.42 | 66000 | 3.2544 |
0.6286 | 3.47 | 67000 | 2.6208 |
0.739 | 3.53 | 68000 | 2.8107 |
0.5981 | 3.58 | 69000 | 2.8073 |
0.6502 | 3.63 | 70000 | 2.6293 |
0.6548 | 3.68 | 71000 | 2.9501 |
0.7243 | 3.73 | 72000 | 2.7917 |
0.598 | 3.78 | 73000 | 2.9341 |
0.6159 | 3.84 | 74000 | 2.7629 |
0.5905 | 3.89 | 75000 | 2.6441 |
0.6393 | 3.94 | 76000 | 2.6660 |
0.677 | 3.99 | 77000 | 2.7616 |
0.3281 | 4.04 | 78000 | 3.6873 |
0.4524 | 4.1 | 79000 | 3.3441 |
0.3994 | 4.15 | 80000 | 3.3129 |
0.4686 | 4.2 | 81000 | 3.1813 |
0.5293 | 4.25 | 82000 | 2.9088 |
0.3961 | 4.3 | 83000 | 3.0765 |
0.4406 | 4.35 | 84000 | 3.1254 |
0.401 | 4.41 | 85000 | 3.2415 |
0.4594 | 4.46 | 86000 | 3.0691 |
0.4523 | 4.51 | 87000 | 3.0493 |
0.4719 | 4.56 | 88000 | 3.1352 |
0.4895 | 4.61 | 89000 | 2.8991 |
0.423 | 4.67 | 90000 | 3.1738 |
0.3984 | 4.72 | 91000 | 3.1862 |
0.4206 | 4.77 | 92000 | 3.1213 |
0.4587 | 4.82 | 93000 | 3.0030 |
0.381 | 4.87 | 94000 | 3.3218 |
0.4138 | 4.92 | 95000 | 3.1529 |
0.4003 | 4.98 | 96000 | 3.1375 |
0.2098 | 5.03 | 97000 | 3.7443 |
0.2334 | 5.08 | 98000 | 3.7359 |
0.2534 | 5.13 | 99000 | 3.7814 |
0.3067 | 5.18 | 100000 | 3.7128 |
0.2363 | 5.24 | 101000 | 3.6091 |
0.2652 | 5.29 | 102000 | 3.4015 |
0.3311 | 5.34 | 103000 | 3.4793 |
0.2344 | 5.39 | 104000 | 3.6792 |
0.2741 | 5.44 | 105000 | 3.5385 |
0.2896 | 5.5 | 106000 | 3.8118 |
0.2071 | 5.55 | 107000 | 3.8690 |
0.3023 | 5.6 | 108000 | 3.7087 |
0.3299 | 5.65 | 109000 | 3.4925 |
0.1943 | 5.7 | 110000 | 3.6739 |
0.2488 | 5.75 | 111000 | 3.7614 |
0.3138 | 5.81 | 112000 | 3.5156 |
0.2555 | 5.86 | 113000 | 3.6056 |
0.2918 | 5.91 | 114000 | 3.6533 |
0.2751 | 5.96 | 115000 | 3.6367 |
Framework versions
- Transformers 4.10.0
- Pytorch 1.8.0+cu101
- Datasets 1.11.0
- Tokenizers 0.10.3
- Downloads last month
- 12
Evaluation results
Model card error
This model's model-index metadata is invalid: Schema validation error. properties must have property 'metrics'