File size: 2,597 Bytes
d5fcd48 ecd911f d5fcd48 ecd911f d5fcd48 ecd911f d5fcd48 ecd911f d5fcd48 ecd911f d5fcd48 |
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 |
---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: hBERTv2_mnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MNLI
type: glue
config: mnli
split: validation_matched
args: mnli
metrics:
- name: Accuracy
type: accuracy
value: 0.3522172497965826
---
<!-- 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. -->
# hBERTv2_mnli
This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2](https://huggingface.co/gokuls/bert_12_layer_model_v2) on the GLUE MNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0983
- Accuracy: 0.3522
## 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
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.0992 | 1.0 | 1534 | 1.0996 | 0.3182 |
| 1.0988 | 2.0 | 3068 | 1.0988 | 0.3182 |
| 1.0987 | 3.0 | 4602 | 1.0987 | 0.3274 |
| 1.0986 | 4.0 | 6136 | 1.0987 | 0.3274 |
| 1.0987 | 5.0 | 7670 | 1.0984 | 0.3545 |
| 1.0987 | 6.0 | 9204 | 1.0986 | 0.3274 |
| 1.0986 | 7.0 | 10738 | 1.0986 | 0.3545 |
| 1.0987 | 8.0 | 12272 | 1.0986 | 0.3545 |
| 1.0986 | 9.0 | 13806 | 1.0984 | 0.3545 |
| 1.0986 | 10.0 | 15340 | 1.0983 | 0.3545 |
| 1.0987 | 11.0 | 16874 | 1.0986 | 0.3182 |
| 1.0987 | 12.0 | 18408 | 1.0984 | 0.3182 |
| 1.0986 | 13.0 | 19942 | 1.0983 | 0.3545 |
| 1.0986 | 14.0 | 21476 | 1.0984 | 0.3182 |
| 1.0986 | 15.0 | 23010 | 1.0986 | 0.3545 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.14.0a0+410ce96
- Datasets 2.10.1
- Tokenizers 0.13.2
|