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tinybert-base-uncased-BiLSTM-Optiparam-ADVQA36K-V1
allistair99/tinybert-base-uncased-BiLSTM-Optiparam-ADVQA36K-V1
tinybert-base-uncased-BiLSTM-Optiparam-ADVQA36K-V1 is a machine learning model from allistair99. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- May 16, 2025
- Updated
- May 16, 2025
- SHA
- 8d46fdc6
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. -->
tinybert-base-uncased-BiLSTM-Optiparam-ADVQA36K-V1
This model is a fine-tuned version of allistair99/tinybert-6l-768d-BiLSTM-finetuned-squad-optiparam on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.9656
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: 6
- eval_batch_size: 60
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.0036 | 0.0599 | 100 | 2.5920 |
| 2.8317 | 0.1198 | 200 | 2.5140 |
| 2.7926 | 0.1796 | 300 | 2.5142 |
| 2.7339 | 0.2395 | 400 | 2.4734 |
| 2.7291 | 0.2994 | 500 | 2.4903 |
| 2.7906 | 0.3593 | 600 | 2.4795 |
| 2.641 | 0.4192 | 700 | 2.4862 |
| 2.5682 | 0.4790 | 800 | 2.5682 |
| 2.6871 | 0.5389 | 900 | 2.4674 |
| 2.7482 | 0.5988 | 1000 | 2.4033 |
| 2.6894 | 0.6587 | 1100 | 2.3723 |
| 2.4788 | 0.7186 | 1200 | 2.3302 |
| 2.6424 | 0.7784 | 1300 | 2.4048 |
| 2.6319 | 0.8383 | 1400 | 2.3805 |
| 2.5736 | 0.8982 | 1500 | 2.3620 |
| 2.5958 | 0.9581 | 1600 | 2.3191 |
| 2.2015 | 1.0180 | 1700 | 2.7917 |
| 1.8579 | 1.0778 | 1800 | 2.3981 |
| 1.7857 | 1.1377 | 1900 | 2.6140 |
| 1.7714 | 1.1976 | 2000 | 2.5079 |
| 1.7564 | 1.2575 | 2100 | 2.6297 |
| 1.8162 | 1.3174 | 2200 | 2.5810 |
| 1.7704 | 1.3772 | 2300 | 2.4192 |
| 1.8182 | 1.4371 | 2400 | 2.4714 |
| 1.8095 | 1.4970 | 2500 | 2.6516 |
| 1.9058 | 1.5569 | 2600 | 2.4050 |
| 1.8567 | 1.6168 | 2700 | 2.4032 |
| 1.7526 | 1.6766 | 2800 | 2.4313 |
| 1.6995 | 1.7365 | 2900 | 2.5849 |
| 1.7793 | 1.7964 | 3000 | 2.5520 |
| 1.7435 | 1.8563 | 3100 | 2.4718 |
| 1.8295 | 1.9162 | 3200 | 2.4131 |
| 1.8069 | 1.9760 | 3300 | 2.4696 |
| 1.4409 | 2.0359 | 3400 | 2.9758 |
| 1.2772 | 2.0958 | 3500 | 2.9478 |
| 1.1997 | 2.1557 | 3600 | 2.9533 |
| 1.19 | 2.2156 | 3700 | 2.8930 |
| 1.1831 | 2.2754 | 3800 | 3.0055 |
| 1.1424 | 2.3353 | 3900 | 3.0072 |
| 1.1612 | 2.3952 | 4000 | 2.9198 |
| 1.242 | 2.4551 | 4100 | 2.9932 |
| 1.1113 | 2.5150 | 4200 | 3.0195 |
| 1.2147 | 2.5749 | 4300 | 2.9441 |
| 1.1773 | 2.6347 | 4400 | 2.9556 |
| 1.2346 | 2.6946 | 4500 | 2.9006 |
| 1.1443 | 2.7545 | 4600 | 2.9683 |
| 1.2002 | 2.8144 | 4700 | 2.9800 |
| 1.1385 | 2.8743 | 4800 | 2.9573 |
| 1.2266 | 2.9341 | 4900 | 2.9599 |
| 1.2089 | 2.9940 | 5000 | 2.9656 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.6.0+cu124
- Datasets 2.21.0
- Tokenizers 0.19.1
- Type
- bert
- License
- mit
- Created
- May 16, 2025
- Updated
- May 16, 2025