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---
library_name: transformers
license: mit
base_model: deepset/gbert-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: testner
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. -->
# testner
This model is a fine-tuned version of [deepset/gbert-large](https://huggingface.co/deepset/gbert-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3944
- Precision: 0.2579
- Recall: 0.2364
- F1: 0.2467
- Accuracy: 0.8626
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 229 | 0.5531 | 0.0305 | 0.0133 | 0.0185 | 0.8440 |
| No log | 2.0 | 458 | 0.5008 | 0.1281 | 0.1055 | 0.1157 | 0.8582 |
| 0.5648 | 3.0 | 687 | 0.5616 | 0.1521 | 0.1648 | 0.1582 | 0.8532 |
| 0.5648 | 4.0 | 916 | 0.5269 | 0.1665 | 0.2315 | 0.1937 | 0.8536 |
| 0.2466 | 5.0 | 1145 | 0.6401 | 0.1885 | 0.2073 | 0.1975 | 0.8551 |
| 0.2466 | 6.0 | 1374 | 0.6759 | 0.1944 | 0.2036 | 0.1989 | 0.8592 |
| 0.1155 | 7.0 | 1603 | 0.7172 | 0.1859 | 0.2206 | 0.2018 | 0.8559 |
| 0.1155 | 8.0 | 1832 | 0.8176 | 0.2 | 0.2194 | 0.2092 | 0.8555 |
| 0.0612 | 9.0 | 2061 | 0.8450 | 0.1904 | 0.2315 | 0.2090 | 0.8519 |
| 0.0612 | 10.0 | 2290 | 0.9029 | 0.1895 | 0.2048 | 0.1969 | 0.8535 |
| 0.0376 | 11.0 | 2519 | 0.9917 | 0.2097 | 0.2194 | 0.2145 | 0.8548 |
| 0.0376 | 12.0 | 2748 | 0.9464 | 0.2346 | 0.2485 | 0.2413 | 0.8609 |
| 0.0376 | 13.0 | 2977 | 1.0170 | 0.2295 | 0.2412 | 0.2352 | 0.8585 |
| 0.022 | 14.0 | 3206 | 0.9993 | 0.2259 | 0.2242 | 0.2251 | 0.8590 |
| 0.022 | 15.0 | 3435 | 1.0762 | 0.2194 | 0.2473 | 0.2325 | 0.8528 |
| 0.0152 | 16.0 | 3664 | 1.0343 | 0.2434 | 0.2364 | 0.2399 | 0.8616 |
| 0.0152 | 17.0 | 3893 | 1.0420 | 0.2241 | 0.2388 | 0.2312 | 0.8570 |
| 0.0137 | 18.0 | 4122 | 1.1025 | 0.2214 | 0.2206 | 0.2210 | 0.8610 |
| 0.0137 | 19.0 | 4351 | 1.0975 | 0.2186 | 0.2339 | 0.2260 | 0.8540 |
| 0.0099 | 20.0 | 4580 | 1.1521 | 0.2281 | 0.2436 | 0.2356 | 0.8592 |
| 0.0099 | 21.0 | 4809 | 1.1143 | 0.2080 | 0.2461 | 0.2254 | 0.8527 |
| 0.0084 | 22.0 | 5038 | 1.2333 | 0.2368 | 0.24 | 0.2384 | 0.8567 |
| 0.0084 | 23.0 | 5267 | 1.1713 | 0.2367 | 0.2364 | 0.2365 | 0.8595 |
| 0.0084 | 24.0 | 5496 | 1.2162 | 0.2599 | 0.2315 | 0.2449 | 0.8643 |
| 0.0065 | 25.0 | 5725 | 1.1444 | 0.2467 | 0.2473 | 0.2470 | 0.8600 |
| 0.0065 | 26.0 | 5954 | 1.2645 | 0.2512 | 0.2545 | 0.2529 | 0.8617 |
| 0.0046 | 27.0 | 6183 | 1.2562 | 0.2252 | 0.2255 | 0.2253 | 0.8610 |
| 0.0046 | 28.0 | 6412 | 1.2663 | 0.2516 | 0.2327 | 0.2418 | 0.8615 |
| 0.0043 | 29.0 | 6641 | 1.2686 | 0.2565 | 0.2497 | 0.2531 | 0.8622 |
| 0.0043 | 30.0 | 6870 | 1.2411 | 0.2342 | 0.2521 | 0.2428 | 0.8586 |
| 0.0037 | 31.0 | 7099 | 1.2620 | 0.2553 | 0.2485 | 0.2518 | 0.8626 |
| 0.0037 | 32.0 | 7328 | 1.3049 | 0.2506 | 0.24 | 0.2452 | 0.8593 |
| 0.003 | 33.0 | 7557 | 1.2796 | 0.2516 | 0.2339 | 0.2425 | 0.8633 |
| 0.003 | 34.0 | 7786 | 1.3039 | 0.2484 | 0.2339 | 0.2409 | 0.8625 |
| 0.0025 | 35.0 | 8015 | 1.3241 | 0.2597 | 0.2436 | 0.2514 | 0.8618 |
| 0.0025 | 36.0 | 8244 | 1.3132 | 0.2475 | 0.2436 | 0.2456 | 0.8613 |
| 0.0025 | 37.0 | 8473 | 1.3445 | 0.25 | 0.2388 | 0.2443 | 0.8620 |
| 0.002 | 38.0 | 8702 | 1.3669 | 0.2556 | 0.2339 | 0.2443 | 0.8635 |
| 0.002 | 39.0 | 8931 | 1.3566 | 0.2623 | 0.2448 | 0.2533 | 0.8622 |
| 0.0018 | 40.0 | 9160 | 1.3300 | 0.2447 | 0.2388 | 0.2417 | 0.8620 |
| 0.0018 | 41.0 | 9389 | 1.3311 | 0.2397 | 0.24 | 0.2399 | 0.8624 |
| 0.0019 | 42.0 | 9618 | 1.3368 | 0.2469 | 0.2412 | 0.2440 | 0.8625 |
| 0.0019 | 43.0 | 9847 | 1.3701 | 0.2430 | 0.2412 | 0.2421 | 0.8624 |
| 0.0014 | 44.0 | 10076 | 1.3941 | 0.2286 | 0.2327 | 0.2306 | 0.8619 |
| 0.0014 | 45.0 | 10305 | 1.3842 | 0.2506 | 0.2352 | 0.2427 | 0.8628 |
| 0.0013 | 46.0 | 10534 | 1.3827 | 0.2443 | 0.2327 | 0.2384 | 0.8619 |
| 0.0013 | 47.0 | 10763 | 1.3730 | 0.2506 | 0.2376 | 0.2439 | 0.8632 |
| 0.0013 | 48.0 | 10992 | 1.3936 | 0.2586 | 0.2364 | 0.2470 | 0.8629 |
| 0.0011 | 49.0 | 11221 | 1.3941 | 0.2634 | 0.2388 | 0.2505 | 0.8627 |
| 0.0011 | 50.0 | 11450 | 1.3944 | 0.2579 | 0.2364 | 0.2467 | 0.8626 |
### Framework versions
- Transformers 4.48.1
- Pytorch 2.5.1
- Datasets 3.2.0
- Tokenizers 0.21.0
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