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---
library_name: transformers
language:
- en
license: apache-2.0
base_model: gokulsrinivasagan/tinybert_base_train_book_ent_15p_s_init
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: tinybert_base_train_book_ent_15p_s_init_mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
args: mrpc
metrics:
- name: Accuracy
type: accuracy
value: 0.7009803921568627
- name: F1
type: f1
value: 0.8038585209003215
---
<!-- 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. -->
# tinybert_base_train_book_ent_15p_s_init_mrpc
This model is a fine-tuned version of [gokulsrinivasagan/tinybert_base_train_book_ent_15p_s_init](https://huggingface.co/gokulsrinivasagan/tinybert_base_train_book_ent_15p_s_init) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5788
- Accuracy: 0.7010
- F1: 0.8039
- Combined Score: 0.7524
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.626 | 1.0 | 15 | 0.5948 | 0.6936 | 0.8025 | 0.7481 |
| 0.5902 | 2.0 | 30 | 0.5788 | 0.7010 | 0.8039 | 0.7524 |
| 0.5641 | 3.0 | 45 | 0.6338 | 0.6961 | 0.8149 | 0.7555 |
| 0.5567 | 4.0 | 60 | 0.5953 | 0.6912 | 0.7886 | 0.7399 |
| 0.5118 | 5.0 | 75 | 0.6027 | 0.6912 | 0.7928 | 0.7420 |
| 0.4615 | 6.0 | 90 | 0.6786 | 0.6814 | 0.7774 | 0.7294 |
| 0.4065 | 7.0 | 105 | 0.7486 | 0.6789 | 0.7835 | 0.7312 |
### Framework versions
- Transformers 4.51.2
- Pytorch 2.6.0+cu126
- Datasets 3.5.0
- Tokenizers 0.21.1
|