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--- |
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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: bert_12_layer_model_v1_complete_training_new_wt_init_48 |
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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_12_layer_model_v1_complete_training_new_wt_init_48 |
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This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.6168 |
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- Accuracy: 0.5281 |
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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: 1e-05 |
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- train_batch_size: 48 |
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- eval_batch_size: 48 |
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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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- lr_scheduler_warmup_steps: 10000 |
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- num_epochs: 5 |
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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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| 6.4172 | 0.08 | 10000 | 6.3664 | 0.1317 | |
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| 6.1014 | 0.16 | 20000 | 6.0532 | 0.1497 | |
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| 5.8255 | 0.25 | 30000 | 5.7466 | 0.1656 | |
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| 5.0543 | 0.33 | 40000 | 4.7539 | 0.2752 | |
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| 4.1669 | 0.41 | 50000 | 3.8568 | 0.3739 | |
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| 3.7259 | 0.49 | 60000 | 3.4751 | 0.4215 | |
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| 3.4547 | 0.57 | 70000 | 3.2615 | 0.4469 | |
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| 3.2968 | 0.66 | 80000 | 3.1250 | 0.4638 | |
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| 3.1805 | 0.74 | 90000 | 3.0246 | 0.4760 | |
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| 3.0963 | 0.82 | 100000 | 2.9491 | 0.4858 | |
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| 3.0238 | 0.9 | 110000 | 2.8874 | 0.4933 | |
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| 2.9729 | 0.98 | 120000 | 2.8317 | 0.5003 | |
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| 2.9156 | 1.07 | 130000 | 2.7824 | 0.5063 | |
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| 2.8784 | 1.15 | 140000 | 2.7434 | 0.5111 | |
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| 2.8333 | 1.23 | 150000 | 2.7081 | 0.5164 | |
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| 2.8043 | 1.31 | 160000 | 2.6730 | 0.5205 | |
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| 2.7646 | 1.39 | 170000 | 2.6436 | 0.5248 | |
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| 2.7403 | 1.47 | 180000 | 2.6168 | 0.5281 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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