classify_resume_model
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9521
- Accuracy: 0.8048
- Precision: 0.7451
- F1-score: 0.7275
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: 1.886221353119542e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 499
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | F1-score |
|---|---|---|---|---|---|---|
| No log | 1.0 | 249 | 2.6457 | 0.5312 | 0.4607 | 0.4336 |
| No log | 2.0 | 498 | 0.9521 | 0.8048 | 0.7451 | 0.7275 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Tokenizers 0.19.1
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Inference Providers
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Model tree for LijinDurairaj/classify_resume_model
Base model
distilbert/distilbert-base-uncased