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--- |
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language: |
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- en |
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base_model: gokuls/bert_12_layer_model_v2_complete_training_new_48 |
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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: hBERTv2_new_pretrain_48_ver2_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 WNLI |
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type: glue |
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config: wnli |
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split: validation |
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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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<!-- 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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# hBERTv2_new_pretrain_48_ver2_wnli |
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This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2_complete_training_new_48](https://huggingface.co/gokuls/bert_12_layer_model_v2_complete_training_new_48) on the GLUE WNLI dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6858 |
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- Accuracy: 0.5634 |
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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: 4e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 10 |
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- distributed_type: multi-GPU |
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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: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.8132 | 1.0 | 10 | 0.7425 | 0.4366 | |
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| 0.7131 | 2.0 | 20 | 0.6970 | 0.4366 | |
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| 0.7083 | 3.0 | 30 | 0.6858 | 0.5634 | |
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| 0.6956 | 4.0 | 40 | 0.6939 | 0.5352 | |
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| 0.7103 | 5.0 | 50 | 0.7313 | 0.4366 | |
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| 0.7169 | 6.0 | 60 | 0.7041 | 0.4366 | |
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| 0.7039 | 7.0 | 70 | 0.6862 | 0.5634 | |
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| 0.7041 | 8.0 | 80 | 0.6919 | 0.5352 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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