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update model card README.md

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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - glue
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: albert-large-v2-finetuned-wnli
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+ results:
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+ - task:
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+ name: Text Classification
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+ type: text-classification
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+ dataset:
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+ name: glue
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+ type: glue
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+ args: wnli
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.5633802816901409
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # albert-large-v2-finetuned-wnli
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+
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+ This model is a fine-tuned version of [albert-large-v2](https://huggingface.co/albert-large-v2) on the glue dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6989
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+ - Accuracy: 0.5634
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 40 | 0.6926 | 0.4648 |
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+ | No log | 2.0 | 80 | 0.6989 | 0.5634 |
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+ | No log | 3.0 | 120 | 0.6870 | 0.5211 |
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+ | No log | 4.0 | 160 | 0.6944 | 0.4930 |
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+ | No log | 5.0 | 200 | 0.7056 | 0.4930 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.15.0
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+ - Pytorch 1.10.0+cu111
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+ - Datasets 1.18.1
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+ - Tokenizers 0.10.3