metadata
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Job_compatibility_model
results: []
Job_compatibility_model
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3397
- Accuracy: 0.8855
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 32 | 0.6822 | 0.5584 |
| No log | 2.0 | 64 | 0.5822 | 0.7009 |
| No log | 3.0 | 96 | 0.3782 | 0.8481 |
| No log | 4.0 | 128 | 0.3534 | 0.8598 |
| No log | 5.0 | 160 | 0.3483 | 0.8575 |
| No log | 6.0 | 192 | 0.3251 | 0.8715 |
| No log | 7.0 | 224 | 0.3170 | 0.8808 |
| No log | 8.0 | 256 | 0.3376 | 0.8715 |
| No log | 9.0 | 288 | 0.3466 | 0.8808 |
| No log | 10.0 | 320 | 0.3397 | 0.8855 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2