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---
tags:
- generated_from_trainer
model-index:
- name: testc8-2
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. -->
# testc8-2
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: 0.2346
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6173 | 1.0 | 16 | 0.3874 |
| 0.5383 | 2.0 | 32 | 0.3227 |
| 0.4756 | 3.0 | 48 | 0.3142 |
| 0.4399 | 4.0 | 64 | 0.3404 |
| 0.4462 | 5.0 | 80 | 0.3112 |
| 0.4187 | 6.0 | 96 | 0.3185 |
| 0.4023 | 7.0 | 112 | 0.2628 |
| 0.3712 | 8.0 | 128 | 0.2807 |
| 0.3922 | 9.0 | 144 | 0.2516 |
| 0.3483 | 10.0 | 160 | 0.1995 |
| 0.3417 | 11.0 | 176 | 0.2452 |
| 0.3585 | 12.0 | 192 | 0.2236 |
| 0.3413 | 13.0 | 208 | 0.2031 |
| 0.3452 | 14.0 | 224 | 0.2238 |
| 0.317 | 15.0 | 240 | 0.2229 |
| 0.3161 | 16.0 | 256 | 0.2591 |
| 0.3338 | 17.0 | 272 | 0.2599 |
| 0.2949 | 18.0 | 288 | 0.2618 |
| 0.3035 | 19.0 | 304 | 0.2436 |
| 0.3108 | 20.0 | 320 | 0.2015 |
| 0.289 | 21.0 | 336 | 0.2329 |
| 0.3144 | 22.0 | 352 | 0.1940 |
| 0.2606 | 23.0 | 368 | 0.2334 |
| 0.2842 | 24.0 | 384 | 0.1996 |
| 0.2892 | 25.0 | 400 | 0.2330 |
| 0.2612 | 26.0 | 416 | 0.2163 |
| 0.2669 | 27.0 | 432 | 0.2053 |
| 0.3147 | 28.0 | 448 | 0.1555 |
| 0.286 | 29.0 | 464 | 0.1983 |
| 0.2857 | 30.0 | 480 | 0.2346 |
### Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
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