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bert-base-uncased-finetuned-autext23_sub2
andricValdez/bert-base-uncased-finetuned-autext23_sub2
bert-base-uncased-finetuned-autext23_sub2 is a machine learning model from andricValdez. 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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At a glance
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Oct 15, 2024
- Updated
- Oct 15, 2024
- SHA
- 1c77c8bb
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. -->
bert-base-uncased-finetuned-autext23_sub2
This model is a fine-tuned version of google-bert/bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2267
- Accuracy: 0.5567
- F1: 0.5503
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 981 | 1.0397 | 0.5251 | 0.5020 |
| 1.0705 | 2.0 | 1962 | 1.0181 | 0.5347 | 0.5225 |
| 1.0705 | 3.0 | 2943 | 1.0734 | 0.5386 | 0.5253 |
| 0.6321 | 4.0 | 3924 | 1.1392 | 0.5548 | 0.5442 |
| 0.6321 | 5.0 | 4905 | 1.2267 | 0.5567 | 0.5503 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
- Type
- bert
- License
- apache-2.0
- Created
- Oct 15, 2024
- Updated
- Oct 15, 2024