readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  - fnet-bert-base-comparison
  datasets:
  - glue
  metrics:
  - spearmanr
  model-index:
  - name: bert-base-cased-finetuned-stsb
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: GLUE STSB
        type: glue
        args: stsb
      metrics:
      - name: Spearmanr
        type: spearmanr
        value: 0.8897907271421561
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # bert-base-cased-finetuned-stsb
  
  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the GLUE STSB dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4861
  - Pearson: 0.8926
  - Spearmanr: 0.8898
  - Combined Score: 0.8912
  
  The model was fine-tuned to compare [google/fnet-base](https://huggingface.co/google/fnet-base) as introduced in [this paper](https://arxiv.org/abs/2105.03824) against [bert-base-cased](https://huggingface.co/bert-base-cased).
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  More information needed
  
  ## Training procedure
  
  This model is trained using the [run_glue](https://github.com/huggingface/transformers/blob/master/examples/pytorch/text-classification/run_glue.py) script. The following command was used:
  
  ```bash
  #!/usr/bin/bash
  
  python ../run_glue.py \\n  --model_name_or_path bert-base-cased \\n  --task_name stsb \\n  --do_train \\n  --do_eval \\n  --max_seq_length 512 \\n  --per_device_train_batch_size 16 \\n  --learning_rate 2e-5 \\n  --num_train_epochs 3 \\n  --output_dir bert-base-cased-finetuned-stsb \\n  --push_to_hub \\n  --hub_strategy all_checkpoints \\n  --logging_strategy epoch \\n  --save_strategy epoch \\n  --evaluation_strategy epoch \\n```
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 2e-05
  - train_batch_size: 16
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3.0
  
  ### Training results
  
  | Training Loss | Epoch | Step | Combined Score | Validation Loss | Pearson | Spearmanr |
  |:-------------:|:-----:|:----:|:--------------:|:---------------:|:-------:|:---------:|
  | 1.1174        | 1.0   | 360  | 0.8816         | 0.5000          | 0.8832  | 0.8800    |
  | 0.3835        | 2.0   | 720  | 0.8901         | 0.4672          | 0.8915  | 0.8888    |
  | 0.2388        | 3.0   | 1080 | 0.8912         | 0.4861          | 0.8926  | 0.8898    |
  
  
  ### Framework versions
  
  - Transformers 4.11.0.dev0
  - Pytorch 1.9.0
  - Datasets 1.12.1
  - Tokenizers 0.10.3
  