File size: 2,783 Bytes
046eec8 1631178 046eec8 1631178 046eec8 1631178 046eec8 1631178 046eec8 1631178 046eec8 1631178 046eec8 533337b 046eec8 533337b 046eec8 533337b 046eec8 |
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 |
---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: add_BERT_no_pretrain_mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
config: mrpc
split: validation
args: mrpc
metrics:
- name: Accuracy
type: accuracy
value: 0.696078431372549
- name: F1
type: f1
value: 0.7933333333333332
---
<!-- 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. -->
# add_BERT_no_pretrain_mrpc
This model is a fine-tuned version of [](https://huggingface.co/) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5912
- Accuracy: 0.6961
- F1: 0.7933
- Combined Score: 0.7447
## 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: 4e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 10
- distributed_type: multi-GPU
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6854 | 1.0 | 29 | 0.6711 | 0.6838 | 0.8122 | 0.7480 |
| 0.6496 | 2.0 | 58 | 0.6802 | 0.6838 | 0.8122 | 0.7480 |
| 0.648 | 3.0 | 87 | 0.6246 | 0.6838 | 0.8122 | 0.7480 |
| 0.6363 | 4.0 | 116 | 0.6174 | 0.6838 | 0.8122 | 0.7480 |
| 0.6049 | 5.0 | 145 | 0.6176 | 0.6593 | 0.7459 | 0.7026 |
| 0.5491 | 6.0 | 174 | 0.6038 | 0.6814 | 0.7950 | 0.7382 |
| 0.5601 | 7.0 | 203 | 0.5912 | 0.6961 | 0.7933 | 0.7447 |
| 0.5505 | 8.0 | 232 | 0.6346 | 0.6716 | 0.7781 | 0.7249 |
| 0.5327 | 9.0 | 261 | 0.6283 | 0.6544 | 0.7531 | 0.7037 |
| 0.529 | 10.0 | 290 | 0.6341 | 0.6520 | 0.7568 | 0.7044 |
| 0.5337 | 11.0 | 319 | 0.6285 | 0.6618 | 0.7579 | 0.7098 |
| 0.5383 | 12.0 | 348 | 0.6322 | 0.6348 | 0.7286 | 0.6817 |
### Framework versions
- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3
|