|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: Anshul15/dfmodel |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: dfmodel_epoch2 |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# dfmodel_epoch2 |
|
|
|
This model is a fine-tuned version of [Anshul15/dfmodel](https://huggingface.co/Anshul15/dfmodel) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0338 |
|
- Accuracy: 0.9942 |
|
|
|
## 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: 0.0001 |
|
- train_batch_size: 1 |
|
- eval_batch_size: 1 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 32 |
|
- total_train_batch_size: 32 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 1.0 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:------:|:----:|:---------------:|:--------:| |
|
| 0.0293 | 0.0126 | 10 | 0.0327 | 0.9956 | |
|
| 0.024 | 0.0252 | 20 | 0.0309 | 0.9951 | |
|
| 0.127 | 0.0378 | 30 | 0.1281 | 0.9813 | |
|
| 0.4263 | 0.0503 | 40 | 0.2368 | 0.9726 | |
|
| 0.2466 | 0.0629 | 50 | 0.3207 | 0.9062 | |
|
| 0.2719 | 0.0755 | 60 | 0.2097 | 0.9404 | |
|
| 0.1887 | 0.0881 | 70 | 0.1495 | 0.9627 | |
|
| 0.1869 | 0.1007 | 80 | 0.2185 | 0.9349 | |
|
| 0.4132 | 0.1133 | 90 | 0.4621 | 0.8806 | |
|
| 0.4159 | 0.1259 | 100 | 0.3518 | 0.8740 | |
|
| 0.6154 | 0.1385 | 110 | 0.6299 | 0.6621 | |
|
| 0.648 | 0.1510 | 120 | 0.6511 | 0.6436 | |
|
| 0.6465 | 0.1636 | 130 | 0.6338 | 0.6565 | |
|
| 0.6395 | 0.1762 | 140 | 0.5977 | 0.6806 | |
|
| 0.4741 | 0.1888 | 150 | 0.3318 | 0.9446 | |
|
| 0.1984 | 0.2014 | 160 | 0.1603 | 0.9684 | |
|
| 0.4746 | 0.2140 | 170 | 0.6173 | 0.6776 | |
|
| 0.7002 | 0.2266 | 180 | 0.8941 | 0.3718 | |
|
| 0.7262 | 0.2392 | 190 | 0.6556 | 0.6282 | |
|
| 0.5961 | 0.2517 | 200 | 1.2466 | 0.7199 | |
|
| 0.5095 | 0.2643 | 210 | 0.2349 | 0.9509 | |
|
| 0.2088 | 0.2769 | 220 | 0.1043 | 0.9772 | |
|
| 0.0992 | 0.2895 | 230 | 0.0610 | 0.9888 | |
|
| 0.0672 | 0.3021 | 240 | 0.0544 | 0.9906 | |
|
| 0.0636 | 0.3147 | 250 | 0.0571 | 0.9901 | |
|
| 0.0554 | 0.3273 | 260 | 0.0543 | 0.9904 | |
|
| 0.1168 | 0.3398 | 270 | 0.0621 | 0.9893 | |
|
| 0.1208 | 0.3524 | 280 | 0.0847 | 0.9841 | |
|
| 0.0963 | 0.3650 | 290 | 0.0879 | 0.9819 | |
|
| 0.0666 | 0.3776 | 300 | 0.0606 | 0.9882 | |
|
| 0.0548 | 0.3902 | 310 | 0.0532 | 0.9898 | |
|
| 0.0518 | 0.4028 | 320 | 0.0512 | 0.9904 | |
|
| 0.0411 | 0.4154 | 330 | 0.0580 | 0.9869 | |
|
| 0.062 | 0.4280 | 340 | 0.0427 | 0.9906 | |
|
| 0.0524 | 0.4405 | 350 | 0.0450 | 0.9913 | |
|
| 0.0065 | 0.4531 | 360 | 0.0566 | 0.9898 | |
|
| 0.0564 | 0.4657 | 370 | 0.0579 | 0.9887 | |
|
| 0.0171 | 0.4783 | 380 | 0.0402 | 0.9929 | |
|
| 0.0057 | 0.4909 | 390 | 0.0382 | 0.9935 | |
|
| 0.0209 | 0.5035 | 400 | 0.0420 | 0.9929 | |
|
| 0.0216 | 0.5161 | 410 | 0.0425 | 0.9926 | |
|
| 0.0405 | 0.5287 | 420 | 0.0426 | 0.9926 | |
|
| 0.0213 | 0.5412 | 430 | 0.0421 | 0.9924 | |
|
| 0.0037 | 0.5538 | 440 | 0.0430 | 0.9924 | |
|
| 0.0746 | 0.5664 | 450 | 0.0377 | 0.9939 | |
|
| 0.0394 | 0.5790 | 460 | 0.0799 | 0.9866 | |
|
| 0.1058 | 0.5916 | 470 | 0.0349 | 0.9939 | |
|
| 0.0069 | 0.6042 | 480 | 0.0328 | 0.9943 | |
|
| 0.023 | 0.6168 | 490 | 0.0380 | 0.9929 | |
|
| 0.0642 | 0.6294 | 500 | 0.0328 | 0.9942 | |
|
| 0.0234 | 0.6419 | 510 | 0.0331 | 0.9942 | |
|
| 0.008 | 0.6545 | 520 | 0.0336 | 0.9943 | |
|
| 0.0051 | 0.6671 | 530 | 0.0321 | 0.9947 | |
|
| 0.0384 | 0.6797 | 540 | 0.0309 | 0.9951 | |
|
| 0.0207 | 0.6923 | 550 | 0.0324 | 0.9947 | |
|
| 0.0218 | 0.7049 | 560 | 0.0349 | 0.9940 | |
|
| 0.049 | 0.7175 | 570 | 0.0316 | 0.9948 | |
|
| 0.0385 | 0.7300 | 580 | 0.0283 | 0.9953 | |
|
| 0.0209 | 0.7426 | 590 | 0.0292 | 0.9953 | |
|
| 0.1231 | 0.7552 | 600 | 0.0336 | 0.9942 | |
|
| 0.0055 | 0.7678 | 610 | 0.0381 | 0.9935 | |
|
| 0.0552 | 0.7804 | 620 | 0.0386 | 0.9932 | |
|
| 0.0222 | 0.7930 | 630 | 0.0392 | 0.9928 | |
|
| 0.0168 | 0.8056 | 640 | 0.0360 | 0.9935 | |
|
| 0.0381 | 0.8182 | 650 | 0.0281 | 0.9954 | |
|
| 0.0217 | 0.8307 | 660 | 0.0295 | 0.9953 | |
|
| 0.0757 | 0.8433 | 670 | 0.0280 | 0.9954 | |
|
| 0.0382 | 0.8559 | 680 | 0.0300 | 0.9947 | |
|
| 0.0274 | 0.8685 | 690 | 0.0331 | 0.9945 | |
|
| 0.0055 | 0.8811 | 700 | 0.0336 | 0.9942 | |
|
| 0.0866 | 0.8937 | 710 | 0.0337 | 0.9942 | |
|
| 0.0067 | 0.9063 | 720 | 0.0339 | 0.9942 | |
|
| 0.0217 | 0.9189 | 730 | 0.0344 | 0.9939 | |
|
| 0.0216 | 0.9314 | 740 | 0.0344 | 0.9939 | |
|
| 0.0594 | 0.9440 | 750 | 0.0346 | 0.9939 | |
|
| 0.0056 | 0.9566 | 760 | 0.0342 | 0.9940 | |
|
| 0.0703 | 0.9692 | 770 | 0.0341 | 0.9940 | |
|
| 0.0535 | 0.9818 | 780 | 0.0340 | 0.9940 | |
|
| 0.0416 | 0.9944 | 790 | 0.0338 | 0.9942 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.45.0.dev0 |
|
- Pytorch 2.1.2 |
|
- Datasets 2.21.1.dev0 |
|
- Tokenizers 0.19.1 |
|
|
