File size: 3,292 Bytes
1772f33 5d42281 1772f33 5d42281 1772f33 5d42281 1772f33 5d42281 1772f33 5d42281 1772f33 |
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 90 91 92 93 94 95 96 97 98 |
---
library_name: transformers
language:
- en
license: apache-2.0
base_model: google/bert_uncased_L-4_H-128_A-2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert_uncased_L-4_H-128_A-2_mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
args: mrpc
metrics:
- name: Accuracy
type: accuracy
value: 0.7573529411764706
- name: F1
type: f1
value: 0.840064620355412
---
<!-- 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. -->
# bert_uncased_L-4_H-128_A-2_mrpc
This model is a fine-tuned version of [google/bert_uncased_L-4_H-128_A-2](https://huggingface.co./google/bert_uncased_L-4_H-128_A-2) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5327
- Accuracy: 0.7574
- F1: 0.8401
- Combined Score: 0.7987
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6437 | 1.0 | 15 | 0.6181 | 0.6838 | 0.8122 | 0.7480 |
| 0.6197 | 2.0 | 30 | 0.6047 | 0.6912 | 0.8158 | 0.7535 |
| 0.595 | 3.0 | 45 | 0.5877 | 0.6985 | 0.8161 | 0.7573 |
| 0.582 | 4.0 | 60 | 0.5687 | 0.7279 | 0.8284 | 0.7782 |
| 0.5617 | 5.0 | 75 | 0.5594 | 0.7279 | 0.8295 | 0.7787 |
| 0.5409 | 6.0 | 90 | 0.5550 | 0.7132 | 0.8208 | 0.7670 |
| 0.5213 | 7.0 | 105 | 0.5417 | 0.7255 | 0.8245 | 0.7750 |
| 0.4968 | 8.0 | 120 | 0.5530 | 0.7328 | 0.8310 | 0.7819 |
| 0.4741 | 9.0 | 135 | 0.5580 | 0.7353 | 0.8333 | 0.7843 |
| 0.4545 | 10.0 | 150 | 0.5390 | 0.7549 | 0.8397 | 0.7973 |
| 0.4366 | 11.0 | 165 | 0.5327 | 0.7574 | 0.8401 | 0.7987 |
| 0.4206 | 12.0 | 180 | 0.5350 | 0.7598 | 0.8424 | 0.8011 |
| 0.397 | 13.0 | 195 | 0.5649 | 0.7549 | 0.8447 | 0.7998 |
| 0.3873 | 14.0 | 210 | 0.5602 | 0.7623 | 0.8482 | 0.8052 |
| 0.3725 | 15.0 | 225 | 0.5622 | 0.7525 | 0.8399 | 0.7962 |
| 0.3506 | 16.0 | 240 | 0.5588 | 0.7525 | 0.8374 | 0.7949 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
|