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---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: distilbert_sa_GLUE_Experiment_logit_kd_pretrain_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: 0.8105166802278275
---
<!-- 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. -->
# distilbert_sa_GLUE_Experiment_logit_kd_pretrain_mnli
This model is a fine-tuned version of [gokuls/distilbert_sa_pre-training-complete](https://huggingface.co/gokuls/distilbert_sa_pre-training-complete) on the GLUE MNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3863
- Accuracy: 0.8105
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.4379 | 1.0 | 1534 | 0.3984 | 0.7976 |
| 0.3845 | 2.0 | 3068 | 0.3953 | 0.8047 |
| 0.359 | 3.0 | 4602 | 0.3935 | 0.8102 |
| 0.3411 | 4.0 | 6136 | 0.3962 | 0.8077 |
| 0.3279 | 5.0 | 7670 | 0.3959 | 0.8172 |
| 0.3189 | 6.0 | 9204 | 0.4018 | 0.8102 |
| 0.3119 | 7.0 | 10738 | 0.4040 | 0.8073 |
| 0.3071 | 8.0 | 12272 | 0.3990 | 0.8175 |
### Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.9.0
- Tokenizers 0.13.2
|