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README.md
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---
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license: apache-2.0
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base_model: bert-base-cased
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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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model-index:
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- name: output
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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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# output
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2749
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- Accuracy: 0.9364
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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: 0.0005
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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: cosine
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- lr_scheduler_warmup_ratio: 0.3
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- num_epochs: 10.0
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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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| 0.2399 | 1.0 | 2500 | 0.2539 | 0.9037 |
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| 0.2454 | 2.0 | 5000 | 0.2753 | 0.9064 |
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| 0.2251 | 3.0 | 7500 | 0.2436 | 0.9167 |
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| 0.1996 | 4.0 | 10000 | 0.2271 | 0.9246 |
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| 0.1845 | 5.0 | 12500 | 0.2116 | 0.9269 |
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| 0.205 | 6.0 | 15000 | 0.1946 | 0.9312 |
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| 0.1352 | 7.0 | 17500 | 0.2233 | 0.9328 |
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| 0.1306 | 8.0 | 20000 | 0.2257 | 0.936 |
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| 0.0849 | 9.0 | 22500 | 0.2582 | 0.9372 |
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| 0.0609 | 10.0 | 25000 | 0.2749 | 0.9364 |
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### Framework versions
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- Transformers 4.32.0.dev0
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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