metadata
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert_12_layer_model_v2
results: []
bert_12_layer_model_v2
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.1091
- Accuracy: 0.5983
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: 5e-05
- 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 |
|---|---|---|---|---|
| 5.4137 | 1.0 | 45772 | 3.1519 | 0.4605 |
| 2.7951 | 2.0 | 91544 | 2.4478 | 0.5519 |
| 2.4298 | 3.0 | 137316 | 2.2522 | 0.5784 |
| 2.2864 | 4.0 | 183088 | 2.1548 | 0.5920 |
| 2.2142 | 5.0 | 228860 | 2.1091 | 0.5983 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.14.0a0+410ce96
- Datasets 2.10.0
- Tokenizers 0.13.2