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lbl-file2-fold0
shreyashvora/lbl-file2-fold0
lbl-file2-fold0 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
- f4e3bfb5
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-fold0
This model is a fine-tuned version of shreyashvora/lbl-file1-fold3 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2090
- Accuracy: 0.6212
- F1: 0.5802
- Precision: 0.6232
- Recall: 0.6212
- 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: 0.1161
- Accuracy Label Label 6: 0.2898
- Accuracy Label Label 7: 0.6071
- Accuracy Label Label 8: 0.0
- Accuracy Label Label 9: 0.9123
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 | 1.3072 | 0.5860 | 0.5406 | 0.6242 | 0.5860 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1196 | 0.1966 | 0.5138 | 0.0 | 0.9460 |
| No log | 0.24 | 250 | 1.2671 | 0.5988 | 0.5552 | 0.6246 | 0.5988 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1196 | 0.2199 | 0.5469 | 0.0 | 0.9366 |
| No log | 0.36 | 375 | 1.2643 | 0.6193 | 0.5750 | 0.6205 | 0.6193 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1473 | 0.1771 | 0.6248 | 0.0 | 0.9026 |
| No log | 0.48 | 500 | 1.1849 | 0.6266 | 0.5855 | 0.6159 | 0.6266 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2010 | 0.2293 | 0.6358 | 0.0 | 0.8947 |
| No log | 0.6 | 625 | 1.2457 | 0.6037 | 0.5567 | 0.6277 | 0.6037 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1092 | 0.1491 | 0.5715 | 0.0 | 0.9334 |
| No log | 0.73 | 750 | 1.2090 | 0.6212 | 0.5802 | 0.6232 | 0.6212 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1161 | 0.2898 | 0.6071 | 0.0 | 0.9123 |
| No log | 0.85 | 875 | 1.2322 | 0.6082 | 0.5662 | 0.6264 | 0.6082 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1334 | 0.2572 | 0.5631 | 0.0 | 0.9346 |
| 0.7405 | 0.97 | 1000 | 1.2014 | 0.6258 | 0.5844 | 0.6243 | 0.6258 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1369 | 0.2693 | 0.6187 | 0.0 | 0.9125 |
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