bert-base-banking77-pt2
This model is a fine-tuned version of bert-base-uncased on the banking77 dataset. It achieves the following results on the evaluation set:
- eval_loss: 4.3984
- eval_f1: 0.0003
- eval_runtime: 300.4394
- eval_samples_per_second: 10.252
- eval_steps_per_second: 0.642
- epoch: 1.0
- step: 626
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Framework versions
- Transformers 4.33.3
- Pytorch 2.1.0
- Datasets 2.12.0
- Tokenizers 0.13.2
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Model tree for tonyla25/bert-base-banking77-pt2
Base model
google-bert/bert-base-uncased