results
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: 1.4283
- Accuracy: 0.6952
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: 7.45e-06
- train_batch_size: 16
- eval_batch_size: 16
- 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 | 179 | 1.0664 | 0.6712 |
| No log | 2.0 | 358 | 1.1817 | 0.6806 |
| 0.118 | 3.0 | 537 | 1.4090 | 0.6681 |
| 0.118 | 4.0 | 716 | 1.4375 | 0.6691 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for tm21cy/albert-emotion-provided-params
Base model
distilbert/distilbert-base-uncased