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--- |
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license: apache-2.0 |
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base_model: bert-large-uncased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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model-index: |
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- name: baseline_nli_bert-large |
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results: [] |
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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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# baseline_nli_bert-large |
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This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9293 |
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- Accuracy: 0.6163 |
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- Precision: 0.6163 |
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- Recall: 0.6163 |
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- F1 Score: 0.6185 |
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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: 3e-06 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 101 |
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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: 6 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:--------:| |
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| 1.0447 | 1.0 | 2583 | 0.9867 | 0.4602 | 0.4602 | 0.4602 | 0.4166 | |
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| 0.9632 | 2.0 | 5166 | 0.9132 | 0.5926 | 0.5926 | 0.5926 | 0.5965 | |
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| 0.9063 | 3.0 | 7749 | 0.8976 | 0.6076 | 0.6076 | 0.6076 | 0.6116 | |
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| 0.846 | 4.0 | 10332 | 0.8826 | 0.6218 | 0.6218 | 0.6218 | 0.6212 | |
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| 0.7975 | 5.0 | 12915 | 0.9189 | 0.6136 | 0.6136 | 0.6136 | 0.6169 | |
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| 0.7605 | 6.0 | 15498 | 0.9293 | 0.6163 | 0.6163 | 0.6163 | 0.6185 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.13.3 |
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