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our_baseline_v2
iTroned/our_baseline_v2
our_baseline_v2 is a machine learning model from iTroned. 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 transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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Public
Updated May 2, 2025
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At a glance
- Library
- transformers
- License
- apache-2.0
- Access
- Public
- Created
- May 2, 2025
- Updated
- May 2, 2025
- SHA
- 190b6f1c
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. -->
our_baseline_v2
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5750
- Accuracy Offensive: 0.8419
- F1 Macro Offensive: 0.8040
- F1 Weighted Offensive: 0.8421
- F1 Macro Total: 0.8040
- F1 Weighted Total: 0.8421
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-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy Offensive | F1 Macro Offensive | F1 Weighted Offensive | F1 Macro Total | F1 Weighted Total |
|---|---|---|---|---|---|---|---|---|
| 0.5711 | 1.0 | 3310 | 0.4628 | 0.7209 | 0.4189 | 0.6040 | 0.4189 | 0.6040 |
| 0.6229 | 2.0 | 6620 | 0.4515 | 0.7209 | 0.4189 | 0.6040 | 0.4189 | 0.6040 |
| 0.6223 | 3.0 | 9930 | 0.5702 | 0.8349 | 0.7869 | 0.8316 | 0.7869 | 0.8316 |
| 0.5896 | 4.0 | 13240 | 0.5750 | 0.8419 | 0.8040 | 0.8421 | 0.8040 | 0.8421 |
| 0.5087 | 5.0 | 16550 | 0.7107 | 0.8302 | 0.7937 | 0.8321 | 0.7937 | 0.8321 |
| 0.4596 | 6.0 | 19860 | 1.0489 | 0.8314 | 0.7802 | 0.8271 | 0.7802 | 0.8271 |
| 0.4073 | 7.0 | 23170 | 1.0985 | 0.8337 | 0.7957 | 0.8346 | 0.7957 | 0.8346 |
| 0.4488 | 8.0 | 26480 | 1.1451 | 0.8023 | 0.7741 | 0.8094 | 0.7741 | 0.8094 |
| 0.3448 | 9.0 | 29790 | 1.1537 | 0.8279 | 0.7898 | 0.8294 | 0.7898 | 0.8294 |
Framework versions
- Transformers 4.50.2
- Pytorch 2.6.0+cu124
- Datasets 3.0.1
- Tokenizers 0.21.1
- Library
- transformers
- License
- apache-2.0
- Created
- May 2, 2025
- Updated
- May 2, 2025