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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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- f1 |
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model-index: |
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- name: albert-base-v2-finetuned-mrpc |
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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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config: mrpc |
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split: validation |
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args: mrpc |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8627450980392157 |
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- name: F1 |
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type: f1 |
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value: 0.900709219858156 |
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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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# albert-base-v2-finetuned-mrpc |
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This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the glue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5610 |
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- Accuracy: 0.8627 |
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- F1: 0.9007 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 95 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| No log | 1.0 | 115 | 0.3358 | 0.8676 | 0.9004 | |
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| No log | 2.0 | 230 | 0.3140 | 0.8676 | 0.9029 | |
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| No log | 3.0 | 345 | 0.3763 | 0.8897 | 0.9201 | |
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| No log | 4.0 | 460 | 0.4980 | 0.8725 | 0.9085 | |
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| 0.2512 | 5.0 | 575 | 0.5610 | 0.8627 | 0.9007 | |
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### Framework versions |
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- Transformers 4.28.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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