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library_name: transformers
language:
- en
base_model: Hartunka/tiny_bert_rand_50_v2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: tiny_bert_rand_50_v2_qqp
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE QQP
type: glue
args: qqp
metrics:
- name: Accuracy
type: accuracy
value: 0.8002226069750186
- name: F1
type: f1
value: 0.7093454244485228
---
<!-- 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. -->
# tiny_bert_rand_50_v2_qqp
This model is a fine-tuned version of [Hartunka/tiny_bert_rand_50_v2](https://huggingface.co/Hartunka/tiny_bert_rand_50_v2) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4242
- Accuracy: 0.8002
- F1: 0.7093
- Combined Score: 0.7548
## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.4957 | 1.0 | 1422 | 0.4536 | 0.7809 | 0.6731 | 0.7270 |
| 0.4098 | 2.0 | 2844 | 0.4242 | 0.8002 | 0.7093 | 0.7548 |
| 0.3539 | 3.0 | 4266 | 0.4246 | 0.8104 | 0.7350 | 0.7727 |
| 0.3091 | 4.0 | 5688 | 0.4351 | 0.8166 | 0.7307 | 0.7736 |
| 0.272 | 5.0 | 7110 | 0.4376 | 0.8204 | 0.7556 | 0.7880 |
| 0.2409 | 6.0 | 8532 | 0.4505 | 0.8220 | 0.7588 | 0.7904 |
| 0.2152 | 7.0 | 9954 | 0.4935 | 0.8275 | 0.7618 | 0.7946 |
### Framework versions
- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1
|