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---
language:
- en
base_model: Hartunka/tiny_bert_rand_100_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: tiny_bert_rand_100_v1_sst2
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE SST2
type: glue
args: sst2
metrics:
- name: Accuracy
type: accuracy
value: 0.8096330275229358
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# tiny_bert_rand_100_v1_sst2
This model is a fine-tuned version of [Hartunka/tiny_bert_rand_100_v1](https://huggingface.co/Hartunka/tiny_bert_rand_100_v1) on the GLUE SST2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4504
- Accuracy: 0.8096
## 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: 5e-05
- train_batch_size: 256
- eval_batch_size: 256
- seed: 10
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4222 | 1.0 | 264 | 0.4504 | 0.8096 |
| 0.2388 | 2.0 | 528 | 0.5902 | 0.7798 |
| 0.1889 | 3.0 | 792 | 0.5326 | 0.7936 |
| 0.1546 | 4.0 | 1056 | 0.5878 | 0.8039 |
| 0.1291 | 5.0 | 1320 | 0.7141 | 0.7890 |
| 0.1088 | 6.0 | 1584 | 0.8532 | 0.7833 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.19.1