readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: albert-large-v2_cls_SentEval-CR
    results: []
  ---
  
  <!-- 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. -->
  
  # albert-large-v2_cls_SentEval-CR
  
  This model is a fine-tuned version of [albert-large-v2](https://huggingface.co/albert-large-v2) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2767
  - Accuracy: 0.9509
  
  ## 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: cosine
  - lr_scheduler_warmup_ratio: 0.2
  - num_epochs: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 1.0   | 189  | 0.2880          | 0.9124   |
  | No log        | 2.0   | 378  | 0.3215          | 0.9097   |
  | 0.3335        | 3.0   | 567  | 0.2229          | 0.9309   |
  | 0.3335        | 4.0   | 756  | 0.2610          | 0.9442   |
  | 0.3335        | 5.0   | 945  | 0.2767          | 0.9509   |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  