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STS-Lora-Fine-Tuning-Capstone-bert-testing-42-with-lower-r-mid
rajevan123/STS-Lora-Fine-Tuning-Capstone-bert-testing-42-with-lower-r-mid
STS-Lora-Fine-Tuning-Capstone-bert-testing-42-with-lower-r-mid is a machine learning model from rajevan123. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- mit
- Access
- Public
- Created
- Mar 25, 2024
- Updated
- Mar 25, 2024
- SHA
- 214586b6
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
STS-Lora-Fine-Tuning-Capstone-bert-testing-42-with-lower-r-mid
This model is a fine-tuned version of dslim/bert-base-NER on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4126
- Accuracy: 0.4199
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: 3e-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: 40
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 90 | 1.7527 | 0.2429 |
| No log | 2.0 | 180 | 1.7436 | 0.2429 |
| No log | 3.0 | 270 | 1.7371 | 0.2429 |
| No log | 4.0 | 360 | 1.7268 | 0.2444 |
| No log | 5.0 | 450 | 1.7015 | 0.2973 |
| 1.6932 | 6.0 | 540 | 1.6853 | 0.2886 |
| 1.6932 | 7.0 | 630 | 1.6676 | 0.2922 |
| 1.6932 | 8.0 | 720 | 1.6423 | 0.3089 |
| 1.6932 | 9.0 | 810 | 1.6182 | 0.3191 |
| 1.6932 | 10.0 | 900 | 1.5953 | 0.3241 |
| 1.6932 | 11.0 | 990 | 1.5797 | 0.3256 |
| 1.5883 | 12.0 | 1080 | 1.5590 | 0.3358 |
| 1.5883 | 13.0 | 1170 | 1.5306 | 0.3539 |
| 1.5883 | 14.0 | 1260 | 1.5157 | 0.3561 |
| 1.5883 | 15.0 | 1350 | 1.4990 | 0.3604 |
| 1.5883 | 16.0 | 1440 | 1.4944 | 0.3611 |
| 1.4756 | 17.0 | 1530 | 1.4822 | 0.3698 |
| 1.4756 | 18.0 | 1620 | 1.4731 | 0.3735 |
| 1.4756 | 19.0 | 1710 | 1.4655 | 0.3756 |
| 1.4756 | 20.0 | 1800 | 1.4603 | 0.3778 |
| 1.4756 | 21.0 | 1890 | 1.4552 | 0.3974 |
| 1.4756 | 22.0 | 1980 | 1.4478 | 0.3930 |
| 1.4113 | 23.0 | 2070 | 1.4439 | 0.3901 |
| 1.4113 | 24.0 | 2160 | 1.4417 | 0.3930 |
| 1.4113 | 25.0 | 2250 | 1.4359 | 0.4075 |
| 1.4113 | 26.0 | 2340 | 1.4316 | 0.4126 |
| 1.4113 | 27.0 | 2430 | 1.4300 | 0.4061 |
| 1.3841 | 28.0 | 2520 | 1.4258 | 0.4141 |
| 1.3841 | 29.0 | 2610 | 1.4237 | 0.4162 |
| 1.3841 | 30.0 | 2700 | 1.4218 | 0.4133 |
| 1.3841 | 31.0 | 2790 | 1.4205 | 0.4213 |
| 1.3841 | 32.0 | 2880 | 1.4189 | 0.4133 |
| 1.3841 | 33.0 | 2970 | 1.4173 | 0.4162 |
| 1.3682 | 34.0 | 3060 | 1.4159 | 0.4220 |
| 1.3682 | 35.0 | 3150 | 1.4146 | 0.4199 |
| 1.3682 | 36.0 | 3240 | 1.4142 | 0.4213 |
| 1.3682 | 37.0 | 3330 | 1.4134 | 0.4213 |
| 1.3682 | 38.0 | 3420 | 1.4129 | 0.4199 |
| 1.3612 | 39.0 | 3510 | 1.4127 | 0.4184 |
| 1.3612 | 40.0 | 3600 | 1.4126 | 0.4199 |
Framework versions
- PEFT 0.10.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Library
- peft
- License
- mit
- Created
- Mar 25, 2024
- Updated
- Mar 25, 2024