metadata
library_name: transformers
base_model: HuggingFaceM4/Florence-2-DocVQA
tags:
- generated_from_trainer
model-index:
- name: florence_ft
results: []
florence_ft
This model is a fine-tuned version of HuggingFaceM4/Florence-2-DocVQA on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0833
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: 5e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
4.4629 | 0.0123 | 25 | 4.6140 |
4.0165 | 0.0245 | 50 | 3.9075 |
3.0887 | 0.0368 | 75 | 2.4186 |
1.3752 | 0.0491 | 100 | 1.4240 |
1.1205 | 0.0613 | 125 | 1.2705 |
1.0809 | 0.0736 | 150 | 1.2144 |
1.0946 | 0.0859 | 175 | 1.1813 |
1.0311 | 0.0982 | 200 | 1.1653 |
1.0611 | 0.1104 | 225 | 1.1503 |
1.0209 | 0.1227 | 250 | 1.1423 |
1.052 | 0.1350 | 275 | 1.1384 |
1.0129 | 0.1472 | 300 | 1.1273 |
0.9764 | 0.1595 | 325 | 1.1218 |
0.9707 | 0.1718 | 350 | 1.1155 |
1.0024 | 0.1840 | 375 | 1.1151 |
1.0446 | 0.1963 | 400 | 1.1112 |
0.9691 | 0.2086 | 425 | 1.1081 |
1.0018 | 0.2209 | 450 | 1.1040 |
0.9806 | 0.2331 | 475 | 1.0989 |
1.0555 | 0.2454 | 500 | 1.0980 |
0.9778 | 0.2577 | 525 | 1.0981 |
0.988 | 0.2699 | 550 | 1.0962 |
0.988 | 0.2822 | 575 | 1.0939 |
0.9572 | 0.2945 | 600 | 1.0969 |
0.9802 | 0.3067 | 625 | 1.0952 |
0.9504 | 0.3190 | 650 | 1.0933 |
1.0194 | 0.3313 | 675 | 1.0948 |
0.9697 | 0.3436 | 700 | 1.0935 |
0.96 | 0.3558 | 725 | 1.0903 |
0.9665 | 0.3681 | 750 | 1.0924 |
0.9895 | 0.3804 | 775 | 1.0920 |
1.004 | 0.3926 | 800 | 1.0914 |
1.0054 | 0.4049 | 825 | 1.0909 |
0.9514 | 0.4172 | 850 | 1.0890 |
0.9996 | 0.4294 | 875 | 1.0906 |
0.99 | 0.4417 | 900 | 1.0896 |
0.9427 | 0.4540 | 925 | 1.0887 |
1.0014 | 0.4663 | 950 | 1.0883 |
0.9639 | 0.4785 | 975 | 1.0864 |
1.0073 | 0.4908 | 1000 | 1.0877 |
0.9895 | 0.5031 | 1025 | 1.0863 |
0.9594 | 0.5153 | 1050 | 1.0841 |
0.9559 | 0.5276 | 1075 | 1.0849 |
1.0034 | 0.5399 | 1100 | 1.0849 |
0.9795 | 0.5521 | 1125 | 1.0844 |
0.9661 | 0.5644 | 1150 | 1.0834 |
0.9533 | 0.5767 | 1175 | 1.0830 |
0.976 | 0.5890 | 1200 | 1.0830 |
0.9932 | 0.6012 | 1225 | 1.0846 |
1.0067 | 0.6135 | 1250 | 1.0861 |
0.9543 | 0.6258 | 1275 | 1.0854 |
0.9733 | 0.6380 | 1300 | 1.0844 |
0.9673 | 0.6503 | 1325 | 1.0837 |
0.9378 | 0.6626 | 1350 | 1.0837 |
0.9713 | 0.6748 | 1375 | 1.0840 |
0.9913 | 0.6871 | 1400 | 1.0838 |
0.9302 | 0.6994 | 1425 | 1.0837 |
0.9873 | 0.7117 | 1450 | 1.0836 |
0.9618 | 0.7239 | 1475 | 1.0835 |
1.0042 | 0.7362 | 1500 | 1.0835 |
0.9627 | 0.7485 | 1525 | 1.0827 |
0.9635 | 0.7607 | 1550 | 1.0827 |
0.9658 | 0.7730 | 1575 | 1.0828 |
0.9446 | 0.7853 | 1600 | 1.0832 |
0.9844 | 0.7975 | 1625 | 1.0833 |
0.9641 | 0.8098 | 1650 | 1.0837 |
1.0 | 0.8221 | 1675 | 1.0835 |
0.9514 | 0.8344 | 1700 | 1.0837 |
1.0094 | 0.8466 | 1725 | 1.0835 |
0.9379 | 0.8589 | 1750 | 1.0834 |
0.9617 | 0.8712 | 1775 | 1.0835 |
0.9674 | 0.8834 | 1800 | 1.0836 |
0.9867 | 0.8957 | 1825 | 1.0838 |
0.9442 | 0.9080 | 1850 | 1.0832 |
0.9603 | 0.9202 | 1875 | 1.0838 |
0.9766 | 0.9325 | 1900 | 1.0833 |
0.9806 | 0.9448 | 1925 | 1.0835 |
0.9676 | 0.9571 | 1950 | 1.0835 |
0.9856 | 0.9693 | 1975 | 1.0838 |
0.9339 | 0.9816 | 2000 | 1.0836 |
0.9553 | 0.9939 | 2025 | 1.0833 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.0.1+cu117
- Tokenizers 0.19.1