dense_eng_100m_mult_het
This model is a fine-tuned version of on the arrow dataset. It achieves the following results on the evaluation set:
- Loss: 4.9199
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 8849
- training_steps: 88495
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 5.3437 | 1.1301 | 10000 | 5.3484 |
| 4.6671 | 2.2601 | 20000 | 4.8006 |
| 4.3398 | 3.3902 | 30000 | 4.6134 |
| 4.0825 | 4.5202 | 40000 | 4.5581 |
| 3.861 | 5.6503 | 50000 | 4.5743 |
| 3.6091 | 6.7804 | 60000 | 4.6403 |
| 3.3689 | 7.9104 | 70000 | 4.7419 |
| 2.8561 | 9.0406 | 80000 | 4.8836 |
Framework versions
- Transformers 4.51.0
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1
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