robbert-L-dbrd-imdb-clapDataset
This model is a fine-tuned version of sytnaxerror/robbert-large-with-dbrd-plus-imdb-mac on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7077
- Accuracy: 0.8391
- F1: 0.8390
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: 256
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 512
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.06
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 6.1319 | 1.0 | 4521 | 0.7491 | 0.8242 | 0.8240 |
| 5.9382 | 2.0 | 9042 | 0.7086 | 0.8386 | 0.8385 |
| 5.7775 | 3.0 | 13563 | 0.7077 | 0.8391 | 0.8390 |
Framework versions
- Transformers 5.5.4
- Pytorch 2.11.0+cu130
- Datasets 4.8.4
- Tokenizers 0.22.2
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