bert-based_cased-finetuned-financial-talk
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.4094
- eval_accuracy: 0.8997
- eval_f1: 0.8994
- eval_precision: 0.8999
- eval_recall: 0.8997
- eval_runtime: 9.6456
- eval_samples_per_second: 426.827
- eval_steps_per_second: 6.739
- epoch: 4.98
- step: 1190
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: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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