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---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert_12_layer_model_v1_complete_training_new_120
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert_12_layer_model_v1_complete_training_new_120
This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_96](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_96) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2643
- Accuracy: 0.5796
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 2.4425 | 0.08 | 10000 | 2.3838 | 0.5641 |
| 2.4415 | 0.16 | 20000 | 2.3705 | 0.5658 |
| 2.4103 | 0.25 | 30000 | 2.3537 | 0.5680 |
| 2.4068 | 0.33 | 40000 | 2.3430 | 0.5696 |
| 2.3823 | 0.41 | 50000 | 2.3249 | 0.5719 |
| 2.3729 | 0.49 | 60000 | 2.3141 | 0.5733 |
| 2.3516 | 0.57 | 70000 | 2.2986 | 0.5751 |
| 2.342 | 0.66 | 80000 | 2.2878 | 0.5764 |
| 2.3265 | 0.74 | 90000 | 2.2734 | 0.5782 |
| 2.3158 | 0.82 | 100000 | 2.2643 | 0.5796 |
### Framework versions
- Transformers 4.30.1
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3
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