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lbl-file2-fold1
shreyashvora/lbl-file2-fold1
lbl-file2-fold1 is a machine learning model from shreyashvora. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Model type
- distilbert
- Access
- Public
- Created
- Jan 18, 2025
- Updated
- Jan 18, 2025
- SHA
- dd2c731f
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. -->
lbl-file2-fold1
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1244
- Accuracy: 0.6552
- F1: 0.6174
- Precision: 0.6482
- Recall: 0.6552
- Accuracy Label Label 0: 0.0
- Accuracy Label Label 1: 0.0
- Accuracy Label Label 2: 0.0
- Accuracy Label Label 3: 0.0
- Accuracy Label Label 4: 0.0
- Accuracy Label Label 5: 0.2283
- Accuracy Label Label 6: 0.3740
- Accuracy Label Label 7: 0.6570
- Accuracy Label Label 8: 0.02
- Accuracy Label Label 9: 0.9131
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Accuracy Label Label 0 | Accuracy Label Label 1 | Accuracy Label Label 2 | Accuracy Label Label 3 | Accuracy Label Label 4 | Accuracy Label Label 5 | Accuracy Label Label 6 | Accuracy Label Label 7 | Accuracy Label Label 8 | Accuracy Label Label 9 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| No log | 0.12 | 125 | 1.1733 | 0.6301 | 0.5906 | 0.6550 | 0.6301 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1925 | 0.3267 | 0.5775 | 0.0267 | 0.9515 |
| No log | 0.24 | 250 | 1.1200 | 0.6527 | 0.6089 | 0.6297 | 0.6527 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2283 | 0.2147 | 0.7340 | 0.02 | 0.8436 |
| No log | 0.36 | 375 | 1.1326 | 0.6632 | 0.6224 | 0.6363 | 0.6632 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2044 | 0.3394 | 0.7328 | 0.0133 | 0.8534 |
| No log | 0.48 | 500 | 1.1316 | 0.6529 | 0.6139 | 0.6445 | 0.6529 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2760 | 0.2985 | 0.6659 | 0.02 | 0.9055 |
| No log | 0.6 | 625 | 1.1551 | 0.6419 | 0.6047 | 0.6504 | 0.6419 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2095 | 0.4213 | 0.6049 | 0.02 | 0.9322 |
| No log | 0.73 | 750 | 1.1244 | 0.6552 | 0.6174 | 0.6482 | 0.6552 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2283 | 0.3740 | 0.6570 | 0.02 | 0.9131 |
| No log | 0.85 | 875 | 1.1022 | 0.6688 | 0.6293 | 0.6392 | 0.6688 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2624 | 0.3439 | 0.7244 | 0.02 | 0.8721 |
| 0.6987 | 0.97 | 1000 | 1.1215 | 0.6612 | 0.6236 | 0.6459 | 0.6612 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2300 | 0.3949 | 0.6752 | 0.0267 | 0.9039 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.13.3
- Type
- distilbert
- Created
- Jan 18, 2025
- Updated
- Jan 18, 2025