metadata
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: add_bert_12_layer_model_complete_training_new
results: []
add_bert_12_layer_model_complete_training_new
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Accuracy: 0.0000
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: 0.0005
- train_batch_size: 64
- eval_batch_size: 64
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0 | 0.11 | 10000 | nan | 0.0000 |
| 0.0 | 0.22 | 20000 | nan | 0.0000 |
| 0.0 | 0.33 | 30000 | nan | 0.0000 |
| 0.0 | 0.44 | 40000 | nan | 0.0000 |
| 0.0 | 0.55 | 50000 | nan | 0.0000 |
| 0.0 | 0.66 | 60000 | nan | 0.0000 |
| 0.0 | 0.76 | 70000 | nan | 0.0000 |
| 0.0 | 0.87 | 80000 | nan | 0.0000 |
| 0.0 | 0.98 | 90000 | nan | 0.0000 |
| 0.0 | 1.09 | 100000 | nan | 0.0000 |
| 0.0 | 1.2 | 110000 | nan | 0.0000 |
| 0.0 | 1.31 | 120000 | nan | 0.0000 |
| 0.0 | 1.42 | 130000 | nan | 0.0000 |
| 0.0 | 1.53 | 140000 | nan | 0.0000 |
Framework versions
- Transformers 4.29.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3