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targeted_baseline_v3_no_hs
iTroned/targeted_baseline_v3_no_hs
targeted_baseline_v3_no_hs 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.
should probably proofread and complete it, then remove this comment. --
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Updated May 18, 2025
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At a glance
- Library
- transformers
- Access
- Public
- Created
- May 18, 2025
- Updated
- May 18, 2025
- SHA
- 4752f771
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. -->
targeted_baseline_v3_no_hs
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9541
- Accuracy Targeted: 0.6259
- F1 Macro Targeted: 0.5357
- F1 Weighted Targeted: 0.5554
- F1 Macro Total: 0.5357
- F1 Weighted Total: 0.5554
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: 6e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 1337
- 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: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy Targeted | F1 Macro Targeted | F1 Weighted Targeted | F1 Macro Total | F1 Weighted Total |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 45 | 0.6786 | 0.4519 | 0.3112 | 0.2813 | 0.3112 | 0.2813 |
| No log | 2.0 | 90 | 0.7143 | 0.5481 | 0.3541 | 0.3882 | 0.3541 | 0.3882 |
| No log | 3.0 | 135 | 0.7534 | 0.5481 | 0.3541 | 0.3882 | 0.3541 | 0.3882 |
| No log | 4.0 | 180 | 0.8283 | 0.5481 | 0.3541 | 0.3882 | 0.3541 | 0.3882 |
| No log | 5.0 | 225 | 0.9085 | 0.5519 | 0.3630 | 0.3964 | 0.3630 | 0.3964 |
| No log | 6.0 | 270 | 0.9082 | 0.6222 | 0.5292 | 0.5494 | 0.5292 | 0.5494 |
| No log | 7.0 | 315 | 0.9541 | 0.6259 | 0.5357 | 0.5554 | 0.5357 | 0.5554 |
| No log | 8.0 | 360 | 1.1943 | 0.5852 | 0.4442 | 0.4711 | 0.4442 | 0.4711 |
| No log | 9.0 | 405 | 1.3552 | 0.5704 | 0.4061 | 0.4362 | 0.4061 | 0.4362 |
| No log | 10.0 | 450 | 1.3356 | 0.6074 | 0.4981 | 0.5207 | 0.4981 | 0.5207 |
| No log | 11.0 | 495 | 1.3556 | 0.6185 | 0.5265 | 0.5466 | 0.5265 | 0.5466 |
| 0.4882 | 12.0 | 540 | 1.5875 | 0.5926 | 0.4646 | 0.4898 | 0.4646 | 0.4898 |
Framework versions
- Transformers 4.50.2
- Pytorch 2.6.0+cu124
- Datasets 3.0.1
- Tokenizers 0.21.1
- Library
- transformers
- Created
- May 18, 2025
- Updated
- May 18, 2025