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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__sst2__train-8-5
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. -->
# distilbert-base-uncased__sst2__train-8-5
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8419
- Accuracy: 0.6172
## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7057 | 1.0 | 3 | 0.6848 | 0.75 |
| 0.6681 | 2.0 | 6 | 0.6875 | 0.5 |
| 0.6591 | 3.0 | 9 | 0.6868 | 0.25 |
| 0.6052 | 4.0 | 12 | 0.6943 | 0.25 |
| 0.557 | 5.0 | 15 | 0.7078 | 0.25 |
| 0.4954 | 6.0 | 18 | 0.7168 | 0.25 |
| 0.4593 | 7.0 | 21 | 0.7185 | 0.25 |
| 0.3936 | 8.0 | 24 | 0.7212 | 0.25 |
| 0.3699 | 9.0 | 27 | 0.6971 | 0.5 |
| 0.2916 | 10.0 | 30 | 0.6827 | 0.5 |
| 0.2511 | 11.0 | 33 | 0.6464 | 0.5 |
| 0.2109 | 12.0 | 36 | 0.6344 | 0.75 |
| 0.1655 | 13.0 | 39 | 0.6377 | 0.75 |
| 0.1412 | 14.0 | 42 | 0.6398 | 0.75 |
| 0.1157 | 15.0 | 45 | 0.6315 | 0.75 |
| 0.0895 | 16.0 | 48 | 0.6210 | 0.75 |
| 0.0783 | 17.0 | 51 | 0.5918 | 0.75 |
| 0.0606 | 18.0 | 54 | 0.5543 | 0.75 |
| 0.0486 | 19.0 | 57 | 0.5167 | 0.75 |
| 0.0405 | 20.0 | 60 | 0.4862 | 0.75 |
| 0.0376 | 21.0 | 63 | 0.4644 | 0.75 |
| 0.0294 | 22.0 | 66 | 0.4497 | 0.75 |
| 0.0261 | 23.0 | 69 | 0.4428 | 0.75 |
| 0.0238 | 24.0 | 72 | 0.4408 | 0.75 |
| 0.0217 | 25.0 | 75 | 0.4392 | 0.75 |
| 0.0187 | 26.0 | 78 | 0.4373 | 0.75 |
| 0.0177 | 27.0 | 81 | 0.4360 | 0.75 |
| 0.0136 | 28.0 | 84 | 0.4372 | 0.75 |
| 0.0144 | 29.0 | 87 | 0.4368 | 0.75 |
| 0.014 | 30.0 | 90 | 0.4380 | 0.75 |
| 0.0137 | 31.0 | 93 | 0.4383 | 0.75 |
| 0.0133 | 32.0 | 96 | 0.4409 | 0.75 |
| 0.013 | 33.0 | 99 | 0.4380 | 0.75 |
| 0.0096 | 34.0 | 102 | 0.4358 | 0.75 |
| 0.012 | 35.0 | 105 | 0.4339 | 0.75 |
| 0.0122 | 36.0 | 108 | 0.4305 | 0.75 |
| 0.0109 | 37.0 | 111 | 0.4267 | 0.75 |
| 0.0121 | 38.0 | 114 | 0.4231 | 0.75 |
| 0.0093 | 39.0 | 117 | 0.4209 | 0.75 |
| 0.0099 | 40.0 | 120 | 0.4199 | 0.75 |
| 0.0091 | 41.0 | 123 | 0.4184 | 0.75 |
| 0.0116 | 42.0 | 126 | 0.4173 | 0.75 |
| 0.01 | 43.0 | 129 | 0.4163 | 0.75 |
| 0.0098 | 44.0 | 132 | 0.4153 | 0.75 |
| 0.0101 | 45.0 | 135 | 0.4155 | 0.75 |
| 0.0088 | 46.0 | 138 | 0.4149 | 0.75 |
| 0.0087 | 47.0 | 141 | 0.4150 | 0.75 |
| 0.0093 | 48.0 | 144 | 0.4147 | 0.75 |
| 0.0081 | 49.0 | 147 | 0.4147 | 0.75 |
| 0.009 | 50.0 | 150 | 0.4150 | 0.75 |
### Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3
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