finetuned-distilbertMy_model
This model is a fine-tuned version of distilbert-base-uncased on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.1288
- Accuracy: 0.939
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: 5e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 125 | 0.2037 | 0.9265 |
No log | 2.0 | 250 | 0.1720 | 0.9335 |
No log | 3.0 | 375 | 0.1349 | 0.9365 |
0.2612 | 4.0 | 500 | 0.1288 | 0.939 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2
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Model tree for nypgd/finetuned-distilbertMy_model
Base model
distilbert/distilbert-base-uncased