File size: 2,889 Bytes
e15b94b 588d4fa e15b94b 588d4fa e15b94b 588d4fa e15b94b |
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 |
---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- super_glue
metrics:
- accuracy
model-index:
- name: superglue_rte-bert-base-uncased
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: super_glue
type: super_glue
config: rte
split: validation
args: rte
metrics:
- name: Accuracy
type: accuracy
value: 0.6739130434782609
---
<!-- 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. -->
# superglue_rte-bert-base-uncased
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the super_glue dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5070
- Accuracy: 0.6739
## 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: 4
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.704 | 1.0 | 623 | 0.6653 | 0.6159 |
| 0.6848 | 2.0 | 1246 | 0.7144 | 0.4203 |
| 0.7083 | 3.0 | 1869 | 0.6922 | 0.5797 |
| 0.7014 | 4.0 | 2492 | 0.7327 | 0.6232 |
| 0.6528 | 5.0 | 3115 | 0.6727 | 0.6522 |
| 0.6471 | 6.0 | 3738 | 0.8413 | 0.6159 |
| 0.5872 | 7.0 | 4361 | 0.8780 | 0.5507 |
| 0.5954 | 8.0 | 4984 | 0.7604 | 0.6377 |
| 0.5566 | 9.0 | 5607 | 0.8578 | 0.6812 |
| 0.5576 | 10.0 | 6230 | 2.0498 | 0.5362 |
| 0.4923 | 11.0 | 6853 | 1.4097 | 0.6304 |
| 0.5688 | 12.0 | 7476 | 1.4146 | 0.6667 |
| 0.433 | 13.0 | 8099 | 1.3354 | 0.6594 |
| 0.4259 | 14.0 | 8722 | 1.3271 | 0.6957 |
| 0.3869 | 15.0 | 9345 | 1.2881 | 0.6812 |
| 0.3641 | 16.0 | 9968 | 1.4485 | 0.6739 |
| 0.3292 | 17.0 | 10591 | 1.3445 | 0.6739 |
| 0.3734 | 18.0 | 11214 | 1.4917 | 0.6739 |
| 0.3227 | 19.0 | 11837 | 1.5281 | 0.6739 |
| 0.3133 | 20.0 | 12460 | 1.5070 | 0.6739 |
### Framework versions
- Transformers 4.32.1
- Pytorch 1.13.0+cu117
- Datasets 2.15.0
- Tokenizers 0.13.3
|