metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
model-index:
- name: BERT_Mod_2
results: []
BERT_Mod_2
This model is a fine-tuned version of distilbert-base-cased on the glue dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.5659
- eval_accuracy: 0.9037
- eval_runtime: 0.3838
- eval_samples_per_second: 2271.724
- eval_steps_per_second: 143.285
- epoch: 0.01
- step: 49
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: 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: 5
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0
- Datasets 2.4.0
- Tokenizers 0.12.1