<!-- 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. -->
distilbert-base-uncased-finetuned-switchboard-2
This model is a fine-tuned version of distilbert-base-uncased on Switchboard dataset. It achieves the following results on the validation set:
- Loss: 0.7090
- Accuracy: 0.7215
- Precision: 0.7176
- Recall: 0.7215
- F1: 0.7188
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.2139 | 1.0 | 370 | 0.8510 | 0.6875 | 0.6831 | 0.6875 | 0.6846 |
| 0.3195 | 2.0 | 740 | 0.7090 | 0.7215 | 0.7176 | 0.7215 | 0.7188 |
Framework versions
- Transformers 4.13.0
- Pytorch 1.13.0+cu116
- Datasets 1.16.1
- Tokenizers 0.10.3
