bert_interview_new
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9106
- Accuracy: 0.7697
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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- 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 |
|---|---|---|---|---|
| 2.5257 | 1.0 | 759 | 2.1260 | 0.4079 |
| 1.9969 | 2.0 | 1518 | 1.7308 | 0.5066 |
| 1.7415 | 3.0 | 2277 | 1.4204 | 0.6316 |
| 1.5223 | 4.0 | 3036 | 1.2385 | 0.6743 |
| 1.3484 | 5.0 | 3795 | 1.1238 | 0.7039 |
| 1.2576 | 6.0 | 4554 | 1.0478 | 0.7336 |
| 1.1427 | 7.0 | 5313 | 0.9814 | 0.7467 |
| 1.0499 | 8.0 | 6072 | 0.9471 | 0.75 |
| 1.0145 | 9.0 | 6831 | 0.9234 | 0.7632 |
| 0.911 | 10.0 | 7590 | 0.9106 | 0.7697 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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Model tree for eskayML/bert_interview_new
Base model
distilbert/distilbert-base-uncased