<!-- 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-moral-ctx-action-conseq
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: 0.1111
- Accuracy: 0.9676
- F1: 0.9676
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: 9.989502318502869e-05
- train_batch_size: 2000
- eval_batch_size: 2000
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
No log | 1.0 | 10 | 0.1569 | 0.9472 | 0.9472 |
No log | 2.0 | 20 | 0.1171 | 0.9636 | 0.9636 |
No log | 3.0 | 30 | 0.1164 | 0.9664 | 0.9664 |
No log | 4.0 | 40 | 0.1117 | 0.9672 | 0.9672 |
No log | 5.0 | 50 | 0.1111 | 0.9676 | 0.9676 |
Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.1
- Datasets 2.0.0
- Tokenizers 0.11.0