File size: 2,531 Bytes
abb8ed2 cd33675 abb8ed2 cd33675 abb8ed2 cd33675 abb8ed2 cd33675 abb8ed2 cd33675 abb8ed2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 | ---
language:
- en
base_model: Hartunka/tiny_bert_km_50_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: tiny_bert_km_50_v1_mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
args: mrpc
metrics:
- name: Accuracy
type: accuracy
value: 0.7034313725490197
- name: F1
type: f1
value: 0.8141321044546851
---
<!-- 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_km_50_v1_mrpc
This model is a fine-tuned version of [Hartunka/tiny_bert_km_50_v1](https://huggingface.co/Hartunka/tiny_bert_km_50_v1) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5948
- Accuracy: 0.7034
- F1: 0.8141
- Combined Score: 0.7588
## 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 | F1 | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6321 | 1.0 | 15 | 0.6046 | 0.6961 | 0.8086 | 0.7524 |
| 0.5989 | 2.0 | 30 | 0.6043 | 0.6936 | 0.8143 | 0.7539 |
| 0.5748 | 3.0 | 45 | 0.5989 | 0.7010 | 0.8185 | 0.7597 |
| 0.5524 | 4.0 | 60 | 0.5948 | 0.7034 | 0.8141 | 0.7588 |
| 0.5052 | 5.0 | 75 | 0.6063 | 0.6936 | 0.7934 | 0.7435 |
| 0.4327 | 6.0 | 90 | 0.6554 | 0.6887 | 0.7776 | 0.7332 |
| 0.3584 | 7.0 | 105 | 0.7307 | 0.7059 | 0.7924 | 0.7491 |
| 0.258 | 8.0 | 120 | 0.8256 | 0.6936 | 0.7856 | 0.7396 |
| 0.1754 | 9.0 | 135 | 0.9983 | 0.6765 | 0.7617 | 0.7191 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.19.1
|