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BERTModified-rawbert-finetuned-wikitext-test
Sreelalvarier/BERTModified-rawbert-finetuned-wikitext-test
BERTModified-rawbert-finetuned-wikitext-test is a machine learning model from Sreelalvarier. 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 apache-2.0.
should probably proofread and complete it, then remove this comment. --
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Updated Apr 1, 2024
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Apr 1, 2024
- Updated
- Apr 1, 2024
- SHA
- 1f600328
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. -->
BERTModified-rawbert-finetuned-wikitext-test
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 20.9598
- Precision: 0.0387
- Recall: 0.0387
- F1: 0.0387
- Accuracy: 0.0387
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 21.2559 | 1.0 | 25 | 21.1094 | 0.0121 | 0.0121 | 0.0121 | 0.0121 |
| 18.2119 | 2.0 | 50 | 20.8262 | 0.0145 | 0.0145 | 0.0145 | 0.0145 |
| 15.7553 | 3.0 | 75 | 20.6929 | 0.0169 | 0.0169 | 0.0169 | 0.0169 |
| 13.4714 | 4.0 | 100 | 20.6579 | 0.0266 | 0.0266 | 0.0266 | 0.0266 |
| 11.7546 | 5.0 | 125 | 20.6640 | 0.0266 | 0.0266 | 0.0266 | 0.0266 |
| 10.1859 | 6.0 | 150 | 20.6235 | 0.0206 | 0.0206 | 0.0206 | 0.0206 |
| 8.9318 | 7.0 | 175 | 20.6836 | 0.0266 | 0.0266 | 0.0266 | 0.0266 |
| 7.8875 | 8.0 | 200 | 20.6899 | 0.0278 | 0.0278 | 0.0278 | 0.0278 |
| 6.9846 | 9.0 | 225 | 20.7376 | 0.0314 | 0.0314 | 0.0314 | 0.0314 |
| 6.2595 | 10.0 | 250 | 20.8058 | 0.0339 | 0.0339 | 0.0339 | 0.0339 |
| 5.6063 | 11.0 | 275 | 20.8430 | 0.0326 | 0.0326 | 0.0326 | 0.0326 |
| 5.1992 | 12.0 | 300 | 20.8778 | 0.0339 | 0.0339 | 0.0339 | 0.0339 |
| 4.72 | 13.0 | 325 | 20.9012 | 0.0326 | 0.0326 | 0.0326 | 0.0326 |
| 4.405 | 14.0 | 350 | 20.9282 | 0.0363 | 0.0363 | 0.0363 | 0.0363 |
| 4.1 | 15.0 | 375 | 20.9423 | 0.0351 | 0.0351 | 0.0351 | 0.0351 |
| 3.8665 | 16.0 | 400 | 20.9187 | 0.0363 | 0.0363 | 0.0363 | 0.0363 |
| 3.7095 | 17.0 | 425 | 20.9525 | 0.0351 | 0.0351 | 0.0351 | 0.0351 |
| 3.509 | 18.0 | 450 | 20.9430 | 0.0399 | 0.0399 | 0.0399 | 0.0399 |
| 3.5125 | 19.0 | 475 | 20.9929 | 0.0326 | 0.0326 | 0.0326 | 0.0326 |
| 3.4485 | 20.0 | 500 | 20.9752 | 0.0411 | 0.0411 | 0.0411 | 0.0411 |
Framework versions
- Transformers 4.39.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- License
- apache-2.0
- Created
- Apr 1, 2024
- Updated
- Apr 1, 2024