distilbert-base-uncased-finetuned-mi
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: 1.8606
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: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.1069 | 1.0 | 97 | 2.3524 |
| 2.1677 | 2.0 | 194 | 1.9426 |
| 1.9197 | 3.0 | 291 | 2.0536 |
Framework versions
- Transformers 4.16.2
- Pytorch 1.10.1
- Datasets 1.18.3
- Tokenizers 0.11.0
- Downloads last month
- 10
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.