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self_iterative_v1_targeted_iteration_1
iTroned/self_iterative_v1_targeted_iteration_1
self_iterative_v1_targeted_iteration_1 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. --
Access
Public
Updated May 12, 2025
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At a glance
- Library
- transformers
- License
- apache-2.0
- Access
- Public
- Created
- May 11, 2025
- Updated
- May 12, 2025
- SHA
- d89a23f1
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. -->
<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/> <img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/> <img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/> <img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/> <img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>
self_iterative_v1_targeted_iteration_1
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: 2.1250
- Accuracy Targeted: 0.6978
- F1 Macro Targeted: 0.6215
- F1 Weighted Targeted: 0.6819
- F1 Macro Total: 0.6215
- F1 Weighted Total: 0.6819
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 |
|---|---|---|---|---|---|---|---|---|
| 0.7107 | 1.0 | 6698 | 2.1250 | 0.6978 | 0.6215 | 0.6819 | 0.6215 | 0.6819 |
| 0.5302 | 2.0 | 13396 | 3.4563 | 0.6911 | 0.5669 | 0.6494 | 0.5669 | 0.6494 |
| 0.3943 | 3.0 | 20094 | 3.2639 | 0.7089 | 0.6047 | 0.6769 | 0.6047 | 0.6769 |
| 0.2651 | 4.0 | 26792 | 3.4277 | 0.7133 | 0.6033 | 0.6776 | 0.6033 | 0.6776 |
| 0.1706 | 5.0 | 33490 | 4.0998 | 0.7044 | 0.5987 | 0.6719 | 0.5987 | 0.6719 |
| 0.0863 | 6.0 | 40188 | 4.8950 | 0.7044 | 0.5546 | 0.6465 | 0.5546 | 0.6465 |
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 11, 2025
- Updated
- May 12, 2025