metadata
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: train-bioR-concat-gen5
results: []
train-bioR-concat-gen5
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.4270
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: 0.001
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 96
- total_eval_batch_size: 96
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- training_steps: 41949
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.7032 | 0.2384 | 10000 | 1.5264 |
| 0.68 | 0.4768 | 20000 | 1.4609 |
| 0.6677 | 0.7151 | 30000 | 1.4266 |
| 0.6487 | 0.9535 | 40000 | 1.4270 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0