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---
tags:
- generated_from_trainer
model-index:
- name: testc8-1
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. -->
# testc8-1
This model is a fine-tuned version of [shafin/chemical-bert-uncased-finetuned-cust-c2](https://huggingface.co./shafin/chemical-bert-uncased-finetuned-cust-c2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1490
## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.0415 | 1.0 | 16 | 0.1392 |
| 0.0443 | 2.0 | 32 | 0.1289 |
| 0.0471 | 3.0 | 48 | 0.1363 |
| 0.042 | 4.0 | 64 | 0.1598 |
| 0.0452 | 5.0 | 80 | 0.1571 |
| 0.0446 | 6.0 | 96 | 0.1733 |
| 0.0466 | 7.0 | 112 | 0.1301 |
| 0.0391 | 8.0 | 128 | 0.1359 |
| 0.0425 | 9.0 | 144 | 0.1324 |
| 0.0436 | 10.0 | 160 | 0.0939 |
| 0.0406 | 11.0 | 176 | 0.1495 |
| 0.0387 | 12.0 | 192 | 0.1592 |
| 0.0335 | 13.0 | 208 | 0.1118 |
| 0.0413 | 14.0 | 224 | 0.1508 |
| 0.0363 | 15.0 | 240 | 0.1471 |
| 0.0428 | 16.0 | 256 | 0.1721 |
| 0.0384 | 17.0 | 272 | 0.1853 |
| 0.0381 | 18.0 | 288 | 0.1578 |
| 0.0373 | 19.0 | 304 | 0.1707 |
| 0.0351 | 20.0 | 320 | 0.1241 |
| 0.0346 | 21.0 | 336 | 0.1602 |
| 0.0386 | 22.0 | 352 | 0.1207 |
| 0.0274 | 23.0 | 368 | 0.1642 |
| 0.0338 | 24.0 | 384 | 0.1169 |
| 0.0327 | 25.0 | 400 | 0.1461 |
| 0.026 | 26.0 | 416 | 0.1323 |
| 0.0315 | 27.0 | 432 | 0.1403 |
| 0.042 | 28.0 | 448 | 0.1056 |
| 0.0346 | 29.0 | 464 | 0.1186 |
| 0.0294 | 30.0 | 480 | 0.1490 |
### Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
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