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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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model-index:
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- name: bert-medium-mlm-finetuned-imdb
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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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# bert-medium-mlm-finetuned-imdb
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This model is a fine-tuned version of [google/bert_uncased_L-8_H-512_A-8](https://huggingface.co/google/bert_uncased_L-8_H-512_A-8) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.1565
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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-05
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- train_batch_size: 64
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- eval_batch_size: 64
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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: constant
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- num_epochs: 200
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:-----:|:---------------:|
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| 2.4752 | 0.32 | 500 | 2.2958 |
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| 2.4164 | 0.64 | 1000 | 2.2739 |
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| 2.3904 | 0.96 | 1500 | 2.2490 |
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| 2.3531 | 1.28 | 2000 | 2.2429 |
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| 2.3497 | 1.6 | 2500 | 2.2277 |
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| 2.3208 | 1.92 | 3000 | 2.2253 |
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| 2.3035 | 2.24 | 3500 | 2.2126 |
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| 2.2941 | 2.56 | 4000 | 2.2129 |
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| 2.2953 | 2.88 | 4500 | 2.2009 |
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| 2.2682 | 3.2 | 5000 | 2.1931 |
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| 2.2608 | 3.52 | 5500 | 2.1944 |
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| 2.2475 | 3.84 | 6000 | 2.1844 |
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| 2.2347 | 4.16 | 6500 | 2.1790 |
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| 2.2176 | 4.48 | 7000 | 2.1799 |
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| 2.2263 | 4.8 | 7500 | 2.1722 |
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| 2.2187 | 5.12 | 8000 | 2.1809 |
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| 2.1981 | 5.44 | 8500 | 2.1838 |
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| 2.2157 | 5.76 | 9000 | 2.1646 |
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| 2.1879 | 6.08 | 9500 | 2.1666 |
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| 2.194 | 6.4 | 10000 | 2.1639 |
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| 2.1758 | 6.72 | 10500 | 2.1622 |
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| 2.1811 | 7.04 | 11000 | 2.1605 |
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| 2.1662 | 7.36 | 11500 | 2.1543 |
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| 2.1744 | 7.68 | 12000 | 2.1530 |
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| 2.1712 | 8.0 | 12500 | 2.1577 |
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| 2.1528 | 8.32 | 13000 | 2.1597 |
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| 2.1374 | 8.64 | 13500 | 2.1565 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.12.1+cu113
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- Datasets 2.7.1
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- Tokenizers 0.13.2
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