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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: small-vanilla-target-glue-qnli
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. -->
# small-vanilla-target-glue-qnli
This model is a fine-tuned version of [google/bert_uncased_L-4_H-512_A-8](https://huggingface.co/google/bert_uncased_L-4_H-512_A-8) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3458
- Accuracy: 0.8583
## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- training_steps: 5000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.488 | 0.15 | 500 | 0.3901 | 0.8316 |
| 0.4449 | 0.31 | 1000 | 0.3826 | 0.8373 |
| 0.4243 | 0.46 | 1500 | 0.3596 | 0.8448 |
| 0.4133 | 0.61 | 2000 | 0.3663 | 0.8417 |
| 0.4102 | 0.76 | 2500 | 0.3459 | 0.8499 |
| 0.3924 | 0.92 | 3000 | 0.3286 | 0.8585 |
| 0.3539 | 1.07 | 3500 | 0.3467 | 0.8532 |
| 0.3202 | 1.22 | 4000 | 0.3478 | 0.8636 |
| 0.3183 | 1.37 | 4500 | 0.3574 | 0.8514 |
| 0.3215 | 1.53 | 5000 | 0.3458 | 0.8583 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2
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